diff --git a/doc/pub/week39/html/week39-bs.html b/doc/pub/week39/html/week39-bs.html
index fc49a1729..e853e960d 100644
--- a/doc/pub/week39/html/week39-bs.html
+++ b/doc/pub/week39/html/week39-bs.html
@@ -191,7 +191,10 @@ doconce format html week39.do.txt --html_style=bootstrap --pygments_html_style=d
                None,
                'second-moment-of-the-gradient'),
               ('RMS prop', 2, None, 'rms-prop'),
-              ('ADAM optimizer', 2, None, 'adam-optimizer'),
+              ('"ADAM optimizer":"https://arxiv.org/abs/1412.6980"',
+               2,
+               None,
+               'adam-optimizer-https-arxiv-org-abs-1412-6980'),
               ('Practical tips', 2, None, 'practical-tips'),
               ('Automatic differentiation',
                2,
@@ -325,7 +328,7 @@ MathJax.Hub.Config({
      <!-- navigation toc: --> <li><a href="._week39-bs059.html#momentum-parameter" style="font-size: 80%;">Momentum parameter</a></li>
      <!-- navigation toc: --> <li><a href="._week39-bs060.html#second-moment-of-the-gradient" style="font-size: 80%;">Second moment of the gradient</a></li>
      <!-- navigation toc: --> <li><a href="._week39-bs061.html#rms-prop" style="font-size: 80%;">RMS prop</a></li>
-     <!-- navigation toc: --> <li><a href="._week39-bs062.html#adam-optimizer" style="font-size: 80%;">ADAM optimizer</a></li>
+     <!-- navigation toc: --> <li><a href="._week39-bs062.html#adam-optimizer-https-arxiv-org-abs-1412-6980" style="font-size: 80%;">"ADAM optimizer":"https://arxiv.org/abs/1412.6980"</a></li>
      <!-- navigation toc: --> <li><a href="._week39-bs063.html#practical-tips" style="font-size: 80%;">Practical tips</a></li>
      <!-- navigation toc: --> <li><a href="._week39-bs064.html#automatic-differentiation" style="font-size: 80%;">Automatic differentiation</a></li>
      <!-- navigation toc: --> <li><a href="._week39-bs065.html#using-autograd" style="font-size: 80%;">Using autograd</a></li>
diff --git a/doc/pub/week39/html/week39-reveal.html b/doc/pub/week39/html/week39-reveal.html
index c2c9baf9a..0a95369af 100644
--- a/doc/pub/week39/html/week39-reveal.html
+++ b/doc/pub/week39/html/week39-reveal.html
@@ -2155,7 +2155,7 @@ Hessians.
 <p>Recently, a number of methods have been introduced that accomplish
 this by tracking not only the gradient, but also the second moment of
 the gradient. These methods include AdaGrad, AdaDelta, Root Mean Squared Propagation (RMS-Prop), and
-ADAM.
+<a href="https://arxiv.org/abs/1412.6980" target="_blank">ADAM</a>.
 </p>
 </section>
 
@@ -2192,9 +2192,9 @@ learning rate for flat directions.
 </section>
 
 <section>
-<h2 id="adam-optimizer">ADAM optimizer </h2>
+<h2 id="adam-optimizer-https-arxiv-org-abs-1412-6980"><a href="https://arxiv.org/abs/1412.6980" target="_blank">ADAM optimizer</a> </h2>
 
-<p>A related algorithm is the ADAM optimizer. In ADAM, we keep a running
+<p>A related algorithm is the ADAM optimizer. In <a href="https://arxiv.org/abs/1412.6980" target="_blank">ADAM</a>, we keep a running
 average of both the first and second moment of the gradient and use
 this information to adaptively change the learning rate for different
 parameters. In addition to keeping a running average of the first and
diff --git a/doc/pub/week39/html/week39-solarized.html b/doc/pub/week39/html/week39-solarized.html
index 6e235d7fd..cf8a6af8b 100644
--- a/doc/pub/week39/html/week39-solarized.html
+++ b/doc/pub/week39/html/week39-solarized.html
@@ -218,7 +218,10 @@ div.toc p,a {
                None,
                'second-moment-of-the-gradient'),
               ('RMS prop', 2, None, 'rms-prop'),
-              ('ADAM optimizer', 2, None, 'adam-optimizer'),
+              ('"ADAM optimizer":"https://arxiv.org/abs/1412.6980"',
+               2,
+               None,
+               'adam-optimizer-https-arxiv-org-abs-1412-6980'),
               ('Practical tips', 2, None, 'practical-tips'),
               ('Automatic differentiation',
                2,
@@ -2075,7 +2078,7 @@ Hessians.
 <p>Recently, a number of methods have been introduced that accomplish
 this by tracking not only the gradient, but also the second moment of
 the gradient. These methods include AdaGrad, AdaDelta, Root Mean Squared Propagation (RMS-Prop), and
-ADAM.
+<a href="https://arxiv.org/abs/1412.6980" target="_blank">ADAM</a>.
 </p>
 
 <!-- !split --><br><br><br><br><br><br><br><br><br><br>
@@ -2108,9 +2111,9 @@ learning rate for flat directions.
 </p>
 
 <!-- !split --><br><br><br><br><br><br><br><br><br><br>
-<h2 id="adam-optimizer">ADAM optimizer </h2>
+<h2 id="adam-optimizer-https-arxiv-org-abs-1412-6980"><a href="https://arxiv.org/abs/1412.6980" target="_blank">ADAM optimizer</a> </h2>
 
-<p>A related algorithm is the ADAM optimizer. In ADAM, we keep a running
+<p>A related algorithm is the ADAM optimizer. In <a href="https://arxiv.org/abs/1412.6980" target="_blank">ADAM</a>, we keep a running
 average of both the first and second moment of the gradient and use
 this information to adaptively change the learning rate for different
 parameters. In addition to keeping a running average of the first and
diff --git a/doc/pub/week39/html/week39.html b/doc/pub/week39/html/week39.html
index 530f28186..1e49d0904 100644
--- a/doc/pub/week39/html/week39.html
+++ b/doc/pub/week39/html/week39.html
@@ -295,7 +295,10 @@ div.toc p,a {
                None,
                'second-moment-of-the-gradient'),
               ('RMS prop', 2, None, 'rms-prop'),
-              ('ADAM optimizer', 2, None, 'adam-optimizer'),
+              ('"ADAM optimizer":"https://arxiv.org/abs/1412.6980"',
+               2,
+               None,
+               'adam-optimizer-https-arxiv-org-abs-1412-6980'),
               ('Practical tips', 2, None, 'practical-tips'),
               ('Automatic differentiation',
                2,
@@ -2152,7 +2155,7 @@ Hessians.
 <p>Recently, a number of methods have been introduced that accomplish
 this by tracking not only the gradient, but also the second moment of
 the gradient. These methods include AdaGrad, AdaDelta, Root Mean Squared Propagation (RMS-Prop), and
-ADAM.
+<a href="https://arxiv.org/abs/1412.6980" target="_blank">ADAM</a>.
 </p>
 
 <!-- !split --><br><br><br><br><br><br><br><br><br><br>
@@ -2185,9 +2188,9 @@ learning rate for flat directions.
 </p>
 
 <!-- !split --><br><br><br><br><br><br><br><br><br><br>
-<h2 id="adam-optimizer">ADAM optimizer </h2>
+<h2 id="adam-optimizer-https-arxiv-org-abs-1412-6980"><a href="https://arxiv.org/abs/1412.6980" target="_blank">ADAM optimizer</a> </h2>
 
-<p>A related algorithm is the ADAM optimizer. In ADAM, we keep a running
+<p>A related algorithm is the ADAM optimizer. In <a href="https://arxiv.org/abs/1412.6980" target="_blank">ADAM</a>, we keep a running
 average of both the first and second moment of the gradient and use
 this information to adaptively change the learning rate for different
 parameters. In addition to keeping a running average of the first and
diff --git a/doc/pub/week39/ipynb/ipynb-week39-src.tar.gz b/doc/pub/week39/ipynb/ipynb-week39-src.tar.gz
index a9eadf037..81b0905a3 100644
Binary files a/doc/pub/week39/ipynb/ipynb-week39-src.tar.gz and b/doc/pub/week39/ipynb/ipynb-week39-src.tar.gz differ