added html files
This commit is contained in:
mhjensen
@@ -0,0 +1,240 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0010"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec9" class="anchor">Choose a Model and Algorithm </h2>
|
||||
|
||||
<ol>
|
||||
<li> Supervised?</li>
|
||||
<li> Start with the simplest model that fits your problem</li>
|
||||
<li> Start with minimal processing of data</li>
|
||||
</ol>
|
||||
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs009.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs002.html">3</a></li>
|
||||
<li><a href="._summary-bs003.html">4</a></li>
|
||||
<li><a href="._summary-bs004.html">5</a></li>
|
||||
<li><a href="._summary-bs005.html">6</a></li>
|
||||
<li><a href="._summary-bs006.html">7</a></li>
|
||||
<li><a href="._summary-bs007.html">8</a></li>
|
||||
<li><a href="._summary-bs008.html">9</a></li>
|
||||
<li><a href="._summary-bs009.html">10</a></li>
|
||||
<li class="active"><a href="._summary-bs010.html">11</a></li>
|
||||
<li><a href="._summary-bs011.html">12</a></li>
|
||||
<li><a href="._summary-bs012.html">13</a></li>
|
||||
<li><a href="._summary-bs013.html">14</a></li>
|
||||
<li><a href="._summary-bs014.html">15</a></li>
|
||||
<li><a href="._summary-bs015.html">16</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs011.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,258 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0011"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec10" class="anchor">Preparing Your Data </h2>
|
||||
|
||||
<ol>
|
||||
<li> Shuffle your data</li>
|
||||
<li> Mean center your data</li>
|
||||
|
||||
<ul>
|
||||
<li> Why?</li>
|
||||
</ul>
|
||||
|
||||
<li> Normalize the variance</li>
|
||||
|
||||
<ul>
|
||||
<li> Why?</li>
|
||||
</ul>
|
||||
|
||||
<li> <b>Whitening</b></li>
|
||||
|
||||
<ul>
|
||||
<li> Decorrelates data</li>
|
||||
<li> Can be hit or miss</li>
|
||||
</ul>
|
||||
|
||||
<li> When to do train/test split?</li>
|
||||
</ol>
|
||||
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs010.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs003.html">4</a></li>
|
||||
<li><a href="._summary-bs004.html">5</a></li>
|
||||
<li><a href="._summary-bs005.html">6</a></li>
|
||||
<li><a href="._summary-bs006.html">7</a></li>
|
||||
<li><a href="._summary-bs007.html">8</a></li>
|
||||
<li><a href="._summary-bs008.html">9</a></li>
|
||||
<li><a href="._summary-bs009.html">10</a></li>
|
||||
<li><a href="._summary-bs010.html">11</a></li>
|
||||
<li class="active"><a href="._summary-bs011.html">12</a></li>
|
||||
<li><a href="._summary-bs012.html">13</a></li>
|
||||
<li><a href="._summary-bs013.html">14</a></li>
|
||||
<li><a href="._summary-bs014.html">15</a></li>
|
||||
<li><a href="._summary-bs015.html">16</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs012.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,251 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0012"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec11" class="anchor">Which Activation and Weights to Choose in Neural Networks </h2>
|
||||
|
||||
<ol>
|
||||
<li> RELU? ELU?</li>
|
||||
<li> Sigmoid or Tanh?</li>
|
||||
<li> Set all weights to 0?</li>
|
||||
|
||||
<ul>
|
||||
<li> Terrible idea</li>
|
||||
</ul>
|
||||
|
||||
<li> Set all weights to random values?</li>
|
||||
|
||||
<ul>
|
||||
<li> Small random values</li>
|
||||
</ul>
|
||||
|
||||
</ol>
|
||||
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs011.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs004.html">5</a></li>
|
||||
<li><a href="._summary-bs005.html">6</a></li>
|
||||
<li><a href="._summary-bs006.html">7</a></li>
|
||||
<li><a href="._summary-bs007.html">8</a></li>
|
||||
<li><a href="._summary-bs008.html">9</a></li>
|
||||
<li><a href="._summary-bs009.html">10</a></li>
|
||||
<li><a href="._summary-bs010.html">11</a></li>
|
||||
<li><a href="._summary-bs011.html">12</a></li>
|
||||
<li class="active"><a href="._summary-bs012.html">13</a></li>
|
||||
<li><a href="._summary-bs013.html">14</a></li>
|
||||
<li><a href="._summary-bs014.html">15</a></li>
|
||||
<li><a href="._summary-bs015.html">16</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs013.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,253 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0013"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec12" class="anchor">Optimization Methods and Hyperparameters </h2>
|
||||
|
||||
<ol>
|
||||
<li> Stochastic gradient descent
|
||||
|
||||
<ol type="a"></li>
|
||||
<li> Stochastic gradient descent + momentum</li>
|
||||
</ol>
|
||||
|
||||
<li> State-of-the-art approaches:</li>
|
||||
|
||||
<ul>
|
||||
<li> RMSProp</li>
|
||||
<li> Adam</li>
|
||||
</ul>
|
||||
|
||||
</ol>
|
||||
|
||||
Which regularization and hyperparameters? \( L_1 \) or \( L_2 \), soft classifiers, depths of trees and many other. Need to explore a large set of hyperparameters and regularization methods.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs012.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs005.html">6</a></li>
|
||||
<li><a href="._summary-bs006.html">7</a></li>
|
||||
<li><a href="._summary-bs007.html">8</a></li>
|
||||
<li><a href="._summary-bs008.html">9</a></li>
|
||||
<li><a href="._summary-bs009.html">10</a></li>
|
||||
<li><a href="._summary-bs010.html">11</a></li>
|
||||
<li><a href="._summary-bs011.html">12</a></li>
|
||||
<li><a href="._summary-bs012.html">13</a></li>
|
||||
<li class="active"><a href="._summary-bs013.html">14</a></li>
|
||||
<li><a href="._summary-bs014.html">15</a></li>
|
||||
<li><a href="._summary-bs015.html">16</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs014.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,243 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0014"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec13" class="anchor">Resampling </h2>
|
||||
|
||||
<p>
|
||||
When do we resample?
|
||||
|
||||
<ol>
|
||||
<li> Bootstrap</li>
|
||||
<li> Cross-validation</li>
|
||||
<li> Jackknife and many other</li>
|
||||
</ol>
|
||||
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs013.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs006.html">7</a></li>
|
||||
<li><a href="._summary-bs007.html">8</a></li>
|
||||
<li><a href="._summary-bs008.html">9</a></li>
|
||||
<li><a href="._summary-bs009.html">10</a></li>
|
||||
<li><a href="._summary-bs010.html">11</a></li>
|
||||
<li><a href="._summary-bs011.html">12</a></li>
|
||||
<li><a href="._summary-bs012.html">13</a></li>
|
||||
<li><a href="._summary-bs013.html">14</a></li>
|
||||
<li class="active"><a href="._summary-bs014.html">15</a></li>
|
||||
<li><a href="._summary-bs015.html">16</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs015.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,248 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0015"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec14" class="anchor">Other courses on Data science and Machine Learning at UiO </h2>
|
||||
|
||||
<p>
|
||||
The link here <a href="https://www.mn.uio.no/english/research/about/centre-focus/innovation/data-science/studies/" target="_self"><tt>https://www.mn.uio.no/english/research/about/centre-focus/innovation/data-science/studies/</tt></a> gives an excellent overview of courses on Machine learning at UiO.
|
||||
|
||||
<ol>
|
||||
<li> <a href="http://www.uio.no/studier/emner/matnat/math/STK2100/index-eng.html" target="_self">STK2100 Machine learning and statistical methods for prediction and classification</a>.</li>
|
||||
<li> <a href="https://www.uio.no/studier/emner/matnat/ifi/IN3050/index-eng.html" target="_self">IN3050/IN4050 Introduction to Artificial Intelligence and Machine Learning</a>. Introductory course in machine learning and AI with an algorithmic approach.</li>
|
||||
<li> <a href="http://www.uio.no/studier/emner/matnat/math/STK-INF3000/index-eng.html" target="_self">STK-INF3000/4000 Selected Topics in Data Science</a>. The course provides insight into selected contemporary relevant topics within Data Science.</li>
|
||||
<li> <a href="https://www.uio.no/studier/emner/matnat/ifi/IN4080/index.html" target="_self">IN4080 Natural Language Processing</a>. Probabilistic and machine learning techniques applied to natural language processing.</li>
|
||||
<li> <a href="https://www.uio.no/studier/emner/matnat/math/STK-IN4300/index-eng.html" target="_self">STK-IN4300 – Statistical learning methods in Data Science</a>. An advanced introduction to statistical and machine learning. For students with a good mathematics and statistics background.</li>
|
||||
<li> <a href="https://www.uio.no/studier/emner/matnat/ifi/IN-STK5000/index-eng.html" target="_self">IN-STK5000 Adaptive Methods for Data-Based Decision Making</a>. Methods for adaptive collection and processing of data based on machine learning techniques.</li>
|
||||
<li> <a href="https://www.uio.no/studier/emner/matnat/ifi/IN5400/" target="_self">IN5400/INF5860 – Machine Learning for Image Analysis</a>. An introduction to deep learning with particular emphasis on applications within Image analysis, but useful for other application areas too.</li>
|
||||
<li> <a href="https://www.uio.no/studier/emner/matnat/its/TEK5040/" target="_self">TEK5040 – Dyp læring for autonome systemer</a>. The course addresses advanced algorithms and architectures for deep learning with neural networks. The course provides an introduction to how deep-learning techniques can be used in the construction of key parts of advanced autonomous systems that exist in physical environments and cyber environments.</li>
|
||||
</ol>
|
||||
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs014.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs007.html">8</a></li>
|
||||
<li><a href="._summary-bs008.html">9</a></li>
|
||||
<li><a href="._summary-bs009.html">10</a></li>
|
||||
<li><a href="._summary-bs010.html">11</a></li>
|
||||
<li><a href="._summary-bs011.html">12</a></li>
|
||||
<li><a href="._summary-bs012.html">13</a></li>
|
||||
<li><a href="._summary-bs013.html">14</a></li>
|
||||
<li><a href="._summary-bs014.html">15</a></li>
|
||||
<li class="active"><a href="._summary-bs015.html">16</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs016.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,239 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0016"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec15" class="anchor">Additional courses of interest </h2>
|
||||
|
||||
<ol>
|
||||
<li> <a href="https://www.uio.no/studier/emner/matnat/math/STK4051/index-eng.html" target="_self">STK4051 Computational Statistics</a></li>
|
||||
<li> <a href="https://www.uio.no/studier/emner/matnat/math/STK4021/index-eng.html" target="_self">STK4021 Applied Bayesian Analysis and Numerical Methods</a></li>
|
||||
</ol>
|
||||
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs015.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs008.html">9</a></li>
|
||||
<li><a href="._summary-bs009.html">10</a></li>
|
||||
<li><a href="._summary-bs010.html">11</a></li>
|
||||
<li><a href="._summary-bs011.html">12</a></li>
|
||||
<li><a href="._summary-bs012.html">13</a></li>
|
||||
<li><a href="._summary-bs013.html">14</a></li>
|
||||
<li><a href="._summary-bs014.html">15</a></li>
|
||||
<li><a href="._summary-bs015.html">16</a></li>
|
||||
<li class="active"><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs017.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,253 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0017"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec16" class="anchor">What's the future like? </h2>
|
||||
|
||||
<p>
|
||||
Based on multi-layer nonlinear neural networks, deep learning can
|
||||
learn directly from raw data, automatically extract and abstract
|
||||
features from layer to layer, and then achieve the goal of regression,
|
||||
classification, or ranking. Deep learning has made breakthroughs in
|
||||
computer vision, speech processing and natural language, and reached
|
||||
or even surpassed human level. The success of deep learning is mainly
|
||||
due to the three factors: big data, big model, and big computing.
|
||||
|
||||
<p>
|
||||
In the past few decades, many different architectures of deep neural
|
||||
networks have been proposed, such as
|
||||
|
||||
<ol>
|
||||
<li> Convolutional neural networks, which are mostly used in image and video data processing, and have also been applied to sequential data such as text processing;</li>
|
||||
<li> Recurrent neural networks, which can process sequential data of variable length and have been widely used in natural language understanding and speech processing;</li>
|
||||
<li> Encoder-decoder framework, which is mostly used for image or sequence generation, such as machine translation, text summarization, and image captioning.</li>
|
||||
</ol>
|
||||
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs016.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs009.html">10</a></li>
|
||||
<li><a href="._summary-bs010.html">11</a></li>
|
||||
<li><a href="._summary-bs011.html">12</a></li>
|
||||
<li><a href="._summary-bs012.html">13</a></li>
|
||||
<li><a href="._summary-bs013.html">14</a></li>
|
||||
<li><a href="._summary-bs014.html">15</a></li>
|
||||
<li><a href="._summary-bs015.html">16</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li class="active"><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs018.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,254 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0018"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec17" class="anchor">Reinforcement Learning </h2>
|
||||
|
||||
<p>
|
||||
Reinforcement learning is a sub-area of machine learning. It studies
|
||||
how agents take actions based on trial and error, so as to maximize
|
||||
some notion of cumulative reward in a dynamic system or
|
||||
environment. Due to its generality, the problem has also been studied
|
||||
in many other disciplines, such as game theory, control theory,
|
||||
operations research, information theory, multi-agent systems, swarm
|
||||
intelligence, statistics, and genetic algorithms.
|
||||
|
||||
<p>
|
||||
In March 2016, AlphaGo, a computer program that plays the board game
|
||||
Go, beat Lee Sedol in a five-game match. This was the first time a
|
||||
computer Go program had beaten a 9-dan (highest rank) professional
|
||||
without handicaps. AlphaGo is based on deep convolutional neural
|
||||
networks and reinforcement learning. AlphaGo’s victory was a major
|
||||
milestone in artificial intelligence and it has also made
|
||||
reinforcement learning a hot research area in the field of machine
|
||||
learning.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs017.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs010.html">11</a></li>
|
||||
<li><a href="._summary-bs011.html">12</a></li>
|
||||
<li><a href="._summary-bs012.html">13</a></li>
|
||||
<li><a href="._summary-bs013.html">14</a></li>
|
||||
<li><a href="._summary-bs014.html">15</a></li>
|
||||
<li><a href="._summary-bs015.html">16</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li class="active"><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs019.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,246 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0019"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec18" class="anchor">Transfer learning </h2>
|
||||
|
||||
<p>
|
||||
The goal of transfer learning is to transfer the model or knowledge
|
||||
obtained from a source task to the target task, in order to resolve
|
||||
the issues of insufficient training data in the target task. The
|
||||
rationality of doing so lies in that usually the source and target
|
||||
tasks have inter-correlations, and therefore either the features,
|
||||
samples, or models in the source task might provide useful information
|
||||
for us to better solve the target task. Transfer learning is a hot
|
||||
research topic in recent years, with many problems still waiting to be
|
||||
solved in this space.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs018.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs011.html">12</a></li>
|
||||
<li><a href="._summary-bs012.html">13</a></li>
|
||||
<li><a href="._summary-bs013.html">14</a></li>
|
||||
<li><a href="._summary-bs014.html">15</a></li>
|
||||
<li><a href="._summary-bs015.html">16</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li class="active"><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="._summary-bs028.html">29</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs020.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,246 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0020"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec19" class="anchor">Adversarial learning </h2>
|
||||
|
||||
<p>
|
||||
The conventional deep generative model has a potential problem: the
|
||||
model tends to generate extreme instances to maximize the
|
||||
probabilistic likelihood, which will hurt its performance. Adversarial
|
||||
learning utilizes the adversarial behaviors (e.g., generating
|
||||
adversarial instances or training an adversarial model) to enhance the
|
||||
robustness of the model and improve the quality of the generated
|
||||
data. In recent years, one of the most promising unsupervised learning
|
||||
technologies, generative adversarial networks (GAN), has already been
|
||||
successfully applied to image, speech, and text.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs019.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs012.html">13</a></li>
|
||||
<li><a href="._summary-bs013.html">14</a></li>
|
||||
<li><a href="._summary-bs014.html">15</a></li>
|
||||
<li><a href="._summary-bs015.html">16</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li class="active"><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="._summary-bs028.html">29</a></li>
|
||||
<li><a href="._summary-bs029.html">30</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs021.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,246 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0021"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec20" class="anchor">Dual learning </h2>
|
||||
|
||||
<p>
|
||||
Dual learning is a new learning paradigm, the basic idea of which is
|
||||
to use the primal-dual structure between machine learning tasks to
|
||||
obtain effective feedback/regularization, and guide and strengthen the
|
||||
learning process, thus reducing the requirement of large-scale labeled
|
||||
data for deep learning. The idea of dual learning has been applied to
|
||||
many problems in machine learning, including machine translation,
|
||||
image style conversion, question answering and generation, image
|
||||
classification and generation, text classification and generation,
|
||||
image-to-text, and text-to-image.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs020.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs013.html">14</a></li>
|
||||
<li><a href="._summary-bs014.html">15</a></li>
|
||||
<li><a href="._summary-bs015.html">16</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li class="active"><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="._summary-bs028.html">29</a></li>
|
||||
<li><a href="._summary-bs029.html">30</a></li>
|
||||
<li><a href="._summary-bs030.html">31</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs022.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,241 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0022"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec21" class="anchor">Distributed machine learning </h2>
|
||||
|
||||
<p>
|
||||
Distributed computation will speed up machine learning algorithms,
|
||||
significantly improve their efficiency, and thus enlarge their
|
||||
application. When distributed meets machine learning, more than just
|
||||
implementing the machine learning algorithms in parallel is required.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs021.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs014.html">15</a></li>
|
||||
<li><a href="._summary-bs015.html">16</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li class="active"><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="._summary-bs028.html">29</a></li>
|
||||
<li><a href="._summary-bs029.html">30</a></li>
|
||||
<li><a href="._summary-bs030.html">31</a></li>
|
||||
<li><a href="._summary-bs031.html">32</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs023.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,242 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0023"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec22" class="anchor">Meta learning </h2>
|
||||
|
||||
<p>
|
||||
Meta learning is an emerging research direction in machine
|
||||
learning. Roughly speaking, meta learning concerns learning how to
|
||||
learn, and focuses on the understanding and adaptation of the learning
|
||||
itself, instead of just completing a specific learning task. That is,
|
||||
a meta learner needs to be able to evaluate its own learning methods
|
||||
and adjust its own learning methods according to specific learning
|
||||
tasks.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs022.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs015.html">16</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li class="active"><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="._summary-bs028.html">29</a></li>
|
||||
<li><a href="._summary-bs029.html">30</a></li>
|
||||
<li><a href="._summary-bs030.html">31</a></li>
|
||||
<li><a href="._summary-bs031.html">32</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs024.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,252 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0024"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec23" class="anchor">The Challenges Facing Machine Learning </h2>
|
||||
|
||||
<p>
|
||||
While there has been much progress in machine learning, there are also challenges.
|
||||
|
||||
<p>
|
||||
For example, the mainstream machine learning technologies are
|
||||
black-box approaches, making us concerned about their potential
|
||||
risks. To tackle this challenge, we may want to make machine learning
|
||||
more explainable and controllable. As another example, the
|
||||
computational complexity of machine learning algorithms is usually
|
||||
very high and we may want to invent lightweight algorithms or
|
||||
implementations. Furthermore, in many domains such as physics,
|
||||
chemistry, biology, and social sciences, people usually seek elegantly
|
||||
simple equations (e.g., the Schrödinger equation) to uncover the
|
||||
underlying laws behind various phenomena. In the field of machine
|
||||
learning, can we reveal simple laws instead of designing more complex
|
||||
models for data fitting? Although there are many challenges, we are
|
||||
still very optimistic about the future of machine learning. As we look
|
||||
forward to the future, here are what we think the research hotspots in
|
||||
the next ten years will be.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs023.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs016.html">17</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li class="active"><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="._summary-bs028.html">29</a></li>
|
||||
<li><a href="._summary-bs029.html">30</a></li>
|
||||
<li><a href="._summary-bs030.html">31</a></li>
|
||||
<li><a href="._summary-bs031.html">32</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs025.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,248 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0025"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec24" class="anchor">Explainable machine learning </h2>
|
||||
|
||||
<p>
|
||||
Machine learning, especially deep learning, evolves rapidly. The
|
||||
ability gap between machine and human on many complex cognitive tasks
|
||||
becomes narrower and narrower. However, we are still in the very early
|
||||
stage in terms of explaining why those effective models work and how
|
||||
they work.
|
||||
|
||||
<p>
|
||||
What is missing: the gap between correlation and causation Most
|
||||
machine learning techniques, especially the statistical ones, depend
|
||||
highly on data correlation to make predictions and analyses. In
|
||||
contrast, rational humans tend to reply on clear and trustworthy
|
||||
causality relations obtained via logical reasoning on real and clear
|
||||
facts. It is one of the core goals of explainable machine learning to
|
||||
transition from solving problems by data correlation to solving
|
||||
problems by logical reasoning.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs024.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs017.html">18</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li class="active"><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="._summary-bs028.html">29</a></li>
|
||||
<li><a href="._summary-bs029.html">30</a></li>
|
||||
<li><a href="._summary-bs030.html">31</a></li>
|
||||
<li><a href="._summary-bs031.html">32</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs026.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,250 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0026"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec25" class="anchor">Quantum machine learning </h2>
|
||||
|
||||
<p>
|
||||
Quantum machine learning is an emerging interdisciplinary research
|
||||
area at the intersection of quantum computing and machine learning.
|
||||
|
||||
<p>
|
||||
Quantum computers use effects such as quantum coherence and quantum
|
||||
entanglement to process information, which is fundamentally different
|
||||
from classical computers. Quantum algorithms have surpassed the best
|
||||
classical algorithms in several problems (e.g., searching for an
|
||||
unsorted database, inverting a sparse matrix), which we call quantum
|
||||
acceleration.
|
||||
|
||||
<p>
|
||||
When quantum computing meets machine learning, it can be a mutually
|
||||
beneficial and reinforcing process, as it allows us to take advantage
|
||||
of quantum computing to improve the performance of classical machine
|
||||
learning algorithms. In addition, we can also use the machine learning
|
||||
algorithms (on classic computers) to analyze and improve quantum
|
||||
computing systems.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs025.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs018.html">19</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li class="active"><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="._summary-bs028.html">29</a></li>
|
||||
<li><a href="._summary-bs029.html">30</a></li>
|
||||
<li><a href="._summary-bs030.html">31</a></li>
|
||||
<li><a href="._summary-bs031.html">32</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs027.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,243 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0027"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec26" class="anchor">Quantum machine learning algorithms based on linear algebra </h2>
|
||||
|
||||
<p>
|
||||
Many quantum machine learning algorithms are based on variants of
|
||||
quantum algorithms for solving linear equations, which can efficiently
|
||||
solve N-variable linear equations with complexity of O(log2 N) under
|
||||
certain conditions. The quantum matrix inversion algorithm can
|
||||
accelerate many machine learning methods, such as least square linear
|
||||
regression, least square version of support vector machine, Gaussian
|
||||
process, and more. The training of these algorithms can be simplified
|
||||
to solve linear equations. The key bottleneck of this type of quantum
|
||||
machine learning algorithms is data input—that is, how to initialize
|
||||
the quantum system with the entire data set. Although efficient
|
||||
data-input algorithms exist for certain situations, how to efficiently
|
||||
input data into a quantum system is as yet unknown for most cases.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs026.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs019.html">20</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li class="active"><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="._summary-bs028.html">29</a></li>
|
||||
<li><a href="._summary-bs029.html">30</a></li>
|
||||
<li><a href="._summary-bs030.html">31</a></li>
|
||||
<li><a href="._summary-bs031.html">32</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs028.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,237 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0028"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec27" class="anchor">Quantum reinforcement learning </h2>
|
||||
|
||||
<p>
|
||||
In quantum reinforcement learning, a quantum agent interacts with the
|
||||
classical environment to obtain rewards from the environment, so as to
|
||||
adjust and improve its behavioral strategies. In some cases, it
|
||||
achieves quantum acceleration by the quantum processing capabilities
|
||||
of the agent or the possibility of exploring the environment through
|
||||
quantum superposition. Such algorithms have been proposed in
|
||||
superconducting circuits and systems of trapped ions.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs027.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs020.html">21</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li class="active"><a href="._summary-bs028.html">29</a></li>
|
||||
<li><a href="._summary-bs029.html">30</a></li>
|
||||
<li><a href="._summary-bs030.html">31</a></li>
|
||||
<li><a href="._summary-bs031.html">32</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs029.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,241 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0029"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec28" class="anchor">Quantum deep learning </h2>
|
||||
|
||||
<p>
|
||||
Dedicated quantum information processors, such as quantum annealers
|
||||
and programmable photonic circuits, are well suited for building deep
|
||||
quantum networks. The simplest deep quantum network is the Boltzmann
|
||||
machine. The classical Boltzmann machine consists of bits with tunable
|
||||
interactions and is trained by adjusting the interaction of these bits
|
||||
so that the distribution of its expression conforms to the statistics
|
||||
of the data. To quantize the Boltzmann machine, the neural network can
|
||||
simply be represented as a set of interacting quantum spins that
|
||||
correspond to an adjustable Ising model. Then, by initializing the
|
||||
input neurons in the Boltzmann machine to a fixed state and allowing
|
||||
the system to heat up, we can read out the output qubits to get the
|
||||
result.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs028.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs021.html">22</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="._summary-bs028.html">29</a></li>
|
||||
<li class="active"><a href="._summary-bs029.html">30</a></li>
|
||||
<li><a href="._summary-bs030.html">31</a></li>
|
||||
<li><a href="._summary-bs031.html">32</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs030.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,239 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0030"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec29" class="anchor">Social machine learning </h2>
|
||||
|
||||
<p>
|
||||
Machine learning aims to imitate how humans
|
||||
learn. While we have developed successful machine learning algorithms,
|
||||
until now we have ignored one important fact: humans are social. Each
|
||||
of us is one part of the total society and it is difficult for us to
|
||||
live, learn, and improve ourselves, alone and isolated. Therefore, we
|
||||
should design machines with social properties. Can we let machines
|
||||
evolve by imitating human society so as to achieve more effective,
|
||||
intelligent, interpretable “social machine learning”?
|
||||
|
||||
<p>
|
||||
And much more.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs029.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs022.html">23</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="._summary-bs028.html">29</a></li>
|
||||
<li><a href="._summary-bs029.html">30</a></li>
|
||||
<li class="active"><a href="._summary-bs030.html">31</a></li>
|
||||
<li><a href="._summary-bs031.html">32</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs031.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,232 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0031"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec30" class="anchor">The last words? </h2>
|
||||
|
||||
<p>
|
||||
Early computer scientist Alan Kay said, <b>The best way to predict the
|
||||
future is to create it</b>. Therefore, all machine learning
|
||||
practitioners, whether scholars or engineers, professors or students,
|
||||
need to work together to advance these important research
|
||||
topics. Together, we will not just predict the future, but create it.
|
||||
|
||||
<p>
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs030.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs023.html">24</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="._summary-bs028.html">29</a></li>
|
||||
<li><a href="._summary-bs029.html">30</a></li>
|
||||
<li><a href="._summary-bs030.html">31</a></li>
|
||||
<li class="active"><a href="._summary-bs031.html">32</a></li>
|
||||
<li><a href="._summary-bs032.html">33</a></li>
|
||||
<li><a href="._summary-bs032.html">»</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
@@ -0,0 +1,225 @@
|
||||
<!--
|
||||
Automatically generated HTML file from DocOnce source
|
||||
(https://github.com/hplgit/doconce/)
|
||||
-->
|
||||
<html>
|
||||
<head>
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<meta name="generator" content="DocOnce: https://github.com/hplgit/doconce/" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<meta name="description" content="Summary of course">
|
||||
|
||||
<title>Summary of course</title>
|
||||
|
||||
<!-- Bootstrap style: bootstrap -->
|
||||
<link href="https://netdna.bootstrapcdn.com/bootstrap/3.1.1/css/bootstrap.min.css" rel="stylesheet">
|
||||
<!-- not necessary
|
||||
<link href="https://netdna.bootstrapcdn.com/font-awesome/4.0.3/css/font-awesome.css" rel="stylesheet">
|
||||
-->
|
||||
|
||||
<style type="text/css">
|
||||
|
||||
/* Add scrollbar to dropdown menus in bootstrap navigation bar */
|
||||
.dropdown-menu {
|
||||
height: auto;
|
||||
max-height: 400px;
|
||||
overflow-x: hidden;
|
||||
}
|
||||
|
||||
/* Adds an invisible element before each target to offset for the navigation
|
||||
bar */
|
||||
.anchor::before {
|
||||
content:"";
|
||||
display:block;
|
||||
height:50px; /* fixed header height for style bootstrap */
|
||||
margin:-50px 0 0; /* negative fixed header height */
|
||||
}
|
||||
</style>
|
||||
|
||||
|
||||
</head>
|
||||
|
||||
<!-- tocinfo
|
||||
{'highest level': 2,
|
||||
'sections': [('What? Me worry? No final exam in this course!',
|
||||
2,
|
||||
None,
|
||||
'___sec0'),
|
||||
('What did I learn in school this year?', 2, None, '___sec1'),
|
||||
('Topics we have covered this year', 2, None, '___sec2'),
|
||||
('Statistical analysis and optimization of data',
|
||||
2,
|
||||
None,
|
||||
'___sec3'),
|
||||
('Machine learning', 2, None, '___sec4'),
|
||||
('Learning outcomes and overarching aims of this course',
|
||||
2,
|
||||
None,
|
||||
'___sec5'),
|
||||
('Perspective on Machine Learning', 2, None, '___sec6'),
|
||||
('Machine Learning Research', 2, None, '___sec7'),
|
||||
('Starting your Machine Learning Project', 2, None, '___sec8'),
|
||||
('Choose a Model and Algorithm', 2, None, '___sec9'),
|
||||
('Preparing Your Data', 2, None, '___sec10'),
|
||||
('Which Activation and Weights to Choose in Neural Networks',
|
||||
2,
|
||||
None,
|
||||
'___sec11'),
|
||||
('Optimization Methods and Hyperparameters', 2, None, '___sec12'),
|
||||
('Resampling', 2, None, '___sec13'),
|
||||
('Other courses on Data science and Machine Learning at UiO',
|
||||
2,
|
||||
None,
|
||||
'___sec14'),
|
||||
('Additional courses of interest', 2, None, '___sec15'),
|
||||
("What's the future like?", 2, None, '___sec16'),
|
||||
('Reinforcement Learning', 2, None, '___sec17'),
|
||||
('Transfer learning', 2, None, '___sec18'),
|
||||
('Adversarial learning', 2, None, '___sec19'),
|
||||
('Dual learning', 2, None, '___sec20'),
|
||||
('Distributed machine learning', 2, None, '___sec21'),
|
||||
('Meta learning', 2, None, '___sec22'),
|
||||
('The Challenges Facing Machine Learning', 2, None, '___sec23'),
|
||||
('Explainable machine learning', 2, None, '___sec24'),
|
||||
('Quantum machine learning', 2, None, '___sec25'),
|
||||
('Quantum machine learning algorithms based on linear algebra',
|
||||
2,
|
||||
None,
|
||||
'___sec26'),
|
||||
('Quantum reinforcement learning', 2, None, '___sec27'),
|
||||
('Quantum deep learning', 2, None, '___sec28'),
|
||||
('Social machine learning', 2, None, '___sec29'),
|
||||
('The last words?', 2, None, '___sec30'),
|
||||
('Best wishes to you all and thanks so much for your heroic '
|
||||
'efforts this semester',
|
||||
2,
|
||||
None,
|
||||
'___sec31')]}
|
||||
end of tocinfo -->
|
||||
|
||||
<body>
|
||||
|
||||
|
||||
|
||||
<script type="text/x-mathjax-config">
|
||||
MathJax.Hub.Config({
|
||||
TeX: {
|
||||
equationNumbers: { autoNumber: "none" },
|
||||
extensions: ["AMSmath.js", "AMSsymbols.js", "autobold.js", "color.js"]
|
||||
}
|
||||
});
|
||||
</script>
|
||||
<script type="text/javascript" async
|
||||
src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML">
|
||||
</script>
|
||||
|
||||
|
||||
|
||||
|
||||
<!-- Bootstrap navigation bar -->
|
||||
<div class="navbar navbar-default navbar-fixed-top">
|
||||
<div class="navbar-header">
|
||||
<button type="button" class="navbar-toggle" data-toggle="collapse" data-target=".navbar-responsive-collapse">
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
<span class="icon-bar"></span>
|
||||
</button>
|
||||
<a class="navbar-brand" href="summary-bs.html">Summary of course</a>
|
||||
</div>
|
||||
|
||||
<div class="navbar-collapse collapse navbar-responsive-collapse">
|
||||
<ul class="nav navbar-nav navbar-right">
|
||||
<li class="dropdown">
|
||||
<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
|
||||
<ul class="dropdown-menu">
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs015.html#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Reinforcement Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Transfer learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Adversarial learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Dual learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Distributed machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Meta learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">Explainable machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Quantum machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum reinforcement learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum deep learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Social machine learning</a></li>
|
||||
<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">The last words?</a></li>
|
||||
<!-- navigation toc: --> <li><a href="#___sec31" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
|
||||
|
||||
</ul>
|
||||
</li>
|
||||
</ul>
|
||||
</div>
|
||||
</div>
|
||||
</div> <!-- end of navigation bar -->
|
||||
|
||||
<div class="container">
|
||||
|
||||
<p> </p><p> </p><p> </p> <!-- add vertical space -->
|
||||
|
||||
<a name="part0032"></a>
|
||||
<!-- !split -->
|
||||
|
||||
<h2 id="___sec31" class="anchor">Best wishes to you all and thanks so much for your heroic efforts this semester </h2>
|
||||
|
||||
<p>
|
||||
<br /><br /><center><p><img src="figures/Nebbdyr2.png" align="bottom" width=500></p></center><br /><br />
|
||||
|
||||
<p>
|
||||
<!-- navigation buttons at the bottom of the page -->
|
||||
<ul class="pagination">
|
||||
<li><a href="._summary-bs031.html">«</a></li>
|
||||
<li><a href="._summary-bs000.html">1</a></li>
|
||||
<li><a href="">...</a></li>
|
||||
<li><a href="._summary-bs024.html">25</a></li>
|
||||
<li><a href="._summary-bs025.html">26</a></li>
|
||||
<li><a href="._summary-bs026.html">27</a></li>
|
||||
<li><a href="._summary-bs027.html">28</a></li>
|
||||
<li><a href="._summary-bs028.html">29</a></li>
|
||||
<li><a href="._summary-bs029.html">30</a></li>
|
||||
<li><a href="._summary-bs030.html">31</a></li>
|
||||
<li><a href="._summary-bs031.html">32</a></li>
|
||||
<li class="active"><a href="._summary-bs032.html">33</a></li>
|
||||
</ul>
|
||||
<!-- ------------------- end of main content --------------- -->
|
||||
|
||||
</div> <!-- end container -->
|
||||
<!-- include javascript, jQuery *first* -->
|
||||
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.10.2/jquery.min.js"></script>
|
||||
<script src="https://netdna.bootstrapcdn.com/bootstrap/3.0.0/js/bootstrap.min.js"></script>
|
||||
|
||||
<!-- Bootstrap footer
|
||||
<footer>
|
||||
<a href="http://..."><img width="250" align=right src="http://..."></a>
|
||||
</footer>
|
||||
-->
|
||||
|
||||
|
||||
<center style="font-size:80%">
|
||||
<!-- copyright only on the titlepage -->
|
||||
</center>
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
|
||||
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1,39 @@
|
||||
/**
|
||||
* Touch-based remote controller for your presentation courtesy
|
||||
* of the folks at http://remotes.io
|
||||
*/
|
||||
|
||||
(function(window){
|
||||
|
||||
/**
|
||||
* Detects if we are dealing with a touch enabled device (with some false positives)
|
||||
* Borrowed from modernizr: https://github.com/Modernizr/Modernizr/blob/master/feature-detects/touch.js
|
||||
*/
|
||||
var hasTouch = (function(){
|
||||
return ('ontouchstart' in window) || window.DocumentTouch && document instanceof DocumentTouch;
|
||||
})();
|
||||
|
||||
/**
|
||||
* Detects if notes are enable and the current page is opened inside an /iframe
|
||||
* this prevents loading Remotes.io several times
|
||||
*/
|
||||
var isNotesAndIframe = (function(){
|
||||
return window.RevealNotes && !(self == top);
|
||||
})();
|
||||
|
||||
if(!hasTouch && !isNotesAndIframe){
|
||||
head.ready( 'remotes.ne.min.js', function() {
|
||||
new Remotes("preview")
|
||||
.on("swipe-left", function(e){ Reveal.right(); })
|
||||
.on("swipe-right", function(e){ Reveal.left(); })
|
||||
.on("swipe-up", function(e){ Reveal.down(); })
|
||||
.on("swipe-down", function(e){ Reveal.up(); })
|
||||
.on("tap", function(e){ Reveal.next(); })
|
||||
.on("zoom-out", function(e){ Reveal.toggleOverview(true); })
|
||||
.on("zoom-in", function(e){ Reveal.toggleOverview(false); })
|
||||
;
|
||||
} );
|
||||
|
||||
head.js('https://hakim-static.s3.amazonaws.com/reveal-js/remotes.ne.min.js');
|
||||
}
|
||||
})(window);
|
||||
Reference in New Issue
Block a user