diff --git a/doc/pub/summary/html/._summary-bs000.html b/doc/pub/summary/html/._summary-bs000.html index b9bf38dd4..0cfad85cf 100644 --- a/doc/pub/summary/html/._summary-bs000.html +++ b/doc/pub/summary/html/._summary-bs000.html @@ -72,7 +72,7 @@ Automatically generated HTML file from DocOnce source None, '___sec14'), ('Additional courses of interest', 2, None, '___sec15'), - ('Hot Topics Now', 2, None, '___sec16'), + ("What's the future like?", 2, None, '___sec16'), ('Reinforcement Learning', 2, None, '___sec17'), ('Transfer learning', 2, None, '___sec18'), ('Adversarial learning', 2, None, '___sec19'), @@ -148,7 +148,7 @@ MathJax.Hub.Config({
-
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,
diff --git a/doc/pub/summary/html/summary-solarized.html b/doc/pub/summary/html/summary-solarized.html
index dc99907f6..58e3b5571 100644
--- a/doc/pub/summary/html/summary-solarized.html
+++ b/doc/pub/summary/html/summary-solarized.html
@@ -66,7 +66,7 @@ div { text-align: justify; text-justify: inter-word; }
None,
'___sec14'),
('Additional courses of interest', 2, None, '___sec15'),
- ('Hot Topics Now', 2, None, '___sec16'),
+ ("What's the future like?", 2, None, '___sec16'),
('Reinforcement Learning', 2, None, '___sec17'),
('Transfer learning', 2, None, '___sec18'),
('Adversarial learning', 2, None, '___sec19'),
@@ -390,16 +390,9 @@ The link here Hot Topics Now
-
-
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,
diff --git a/doc/pub/summary/html/summary.html b/doc/pub/summary/html/summary.html
index e2a75ab16..188ab35ba 100644
--- a/doc/pub/summary/html/summary.html
+++ b/doc/pub/summary/html/summary.html
@@ -71,7 +71,7 @@ div { text-align: justify; text-justify: inter-word; }
None,
'___sec14'),
('Additional courses of interest', 2, None, '___sec15'),
- ('Hot Topics Now', 2, None, '___sec16'),
+ ("What's the future like?", 2, None, '___sec16'),
('Reinforcement Learning', 2, None, '___sec17'),
('Transfer learning', 2, None, '___sec18'),
('Adversarial learning', 2, None, '___sec19'),
@@ -395,16 +395,9 @@ The link here Hot Topics Now
-
-
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,
diff --git a/doc/pub/summary/ipynb/ipynb-summary-src.tar.gz b/doc/pub/summary/ipynb/ipynb-summary-src.tar.gz
index dbc79daf1..c190be9d4 100644
Binary files a/doc/pub/summary/ipynb/ipynb-summary-src.tar.gz and b/doc/pub/summary/ipynb/ipynb-summary-src.tar.gz differ
diff --git a/doc/pub/summary/ipynb/summary.ipynb b/doc/pub/summary/ipynb/summary.ipynb
index 3cea2fa8d..a5654f7cf 100644
--- a/doc/pub/summary/ipynb/summary.ipynb
+++ b/doc/pub/summary/ipynb/summary.ipynb
@@ -257,17 +257,7 @@
"\n",
"2. [STK4021 Applied Bayesian Analysis and Numerical Methods](https://www.uio.no/studier/emner/matnat/math/STK4021/index-eng.html)\n",
"\n",
- "## Hot Topics Now\n",
- "\n",
- "1. Boosting techniques and complex neural networks\n",
- "\n",
- "2. [Adversarial examples](https://medium.com/@ml.at.berkeley/trickingneural-networks-create-your-own-adversarial-examples-a61eb7620fd8)\n",
- "\n",
- "3. [Zero shot learning](https://arxiv.org/pdf/1707.00600)\n",
- "\n",
- "4. Transfer learning\n",
- "\n",
- "5. [Model interpretability](https://christophm.github.io/interpretable-mlbook/interpretability.html)\n",
+ "## What's the future like?\n",
"\n",
"Based on multi-layer nonlinear neural networks, deep learning can\n",
"learn directly from raw data, automatically extract and abstract\n",
diff --git a/doc/pub/summary/pdf/summary-minted.pdf b/doc/pub/summary/pdf/summary-minted.pdf
index 50f6829b4..fc6a35364 100644
Binary files a/doc/pub/summary/pdf/summary-minted.pdf and b/doc/pub/summary/pdf/summary-minted.pdf differ
diff --git a/doc/src/Summary/summary.do.txt b/doc/src/Summary/summary.do.txt
index c70b0f5ee..96d40f960 100644
--- a/doc/src/Summary/summary.do.txt
+++ b/doc/src/Summary/summary.do.txt
@@ -185,14 +185,7 @@ o "STK4051 Computational Statistics":"https://www.uio.no/studier/emner/matnat/ma
o "STK4021 Applied Bayesian Analysis and Numerical Methods":"https://www.uio.no/studier/emner/matnat/math/STK4021/index-eng.html"
!split
-===== Hot Topics Now =====
-
-o Boosting techniques and complex neural networks
-o "Adversarial examples":"https://medium.com/@ml.at.berkeley/trickingneural-networks-create-your-own-adversarial-examples-a61eb7620fd8"
-o "Zero shot learning":"https://arxiv.org/pdf/1707.00600"
-o Transfer learning
-o "Model interpretability":"https://christophm.github.io/interpretable-mlbook/interpretability.html"
-
+===== What's the future like? =====
Based on multi-layer nonlinear neural networks, deep learning can
learn directly from raw data, automatically extract and abstract
-
+What's the future like?
+
-
+What's the future like?
+