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<ul>
<li>
<a href="./posts/iclr-2020-notes.html">ICLR 2020 Notes</a> - May 5, 2020
<a href="./posts/iclr-2020-notes.html">ICLR 2020 Notes: Speakers and Workshops</a> - May 5, 2020
</li>
<li>

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</author>
<updated>2020-05-05T00:00:00Z</updated>
<entry>
<title>ICLR 2020 Notes</title>
<title>ICLR 2020 Notes: Speakers and Workshops</title>
<link href="https://www.lozeve.com/posts/iclr-2020-notes.html" />
<id>https://www.lozeve.com/posts/iclr-2020-notes.html</id>
<published>2020-05-05T00:00:00Z</published>
@ -28,7 +28,9 @@
<p>In this post, I will try to give my impressions on the event, and share the most interesting events and papers I saw.</p>
<h1 id="the-format-of-the-virtual-conference">The Format of the Virtual Conference</h1>
<p>As a result of global travel restrictions, the conference was made fully-virtual. It was supposed to take place in Addis Ababa, Ethiopia, which is great for people who are often the target of restrictive visa policies in Northern American countries.</p>
<p>The thing I appreciated most about the conference format was its emphasis on <em>asynchronous</em> communication. Given how little time they had to plan the conference, they could have made all poster presentations via video-conference and call it a day. Instead, each poster had to record a 5-minute video summarising their research. Alongside each presentation, there was a dedicated Rocket.Chat channel<span><label for="sn-2" class="margin-toggle sidenote-number"></label><input type="checkbox" id="sn-2" class="margin-toggle"/><span class="sidenote"><a href="https://rocket.chat/">Rocket.Chat</a> seems to be an <a href="https://github.com/RocketChat/Rocket.Chat">open-source</a> alternative to Slack. Overall, the experience was great, and I appreciate the efforts of the organizers to use open source software instead of proprietary applications. I hope other conferences will do the same, and perhaps even avoid Zoom, because of recent privacy concerns (maybe try <a href="https://jitsi.org/">Jitsi</a>?).<br />
<p>The thing I appreciated most about the conference format was its emphasis on <em>asynchronous</em> communication. Given how little time they had to plan the conference, they could have made all poster presentations via video-conference and call it a day. Instead, each poster had to record a 5-minute video<span><label for="sn-2" class="margin-toggle sidenote-number"></label><input type="checkbox" id="sn-2" class="margin-toggle"/><span class="sidenote">The videos are streamed using <a href="https://library.slideslive.com/">SlidesLive</a>, which is a great solution for synchronising videos and slides. It is very comfortable to navigate through the slides and synchronising the video to the slides and vice-versa. As a result, SlidesLive also has a very nice library of talks, including major conferences. This is much better than browsing YouTube randomly.<br />
<br />
</span></span> summarising their research. Alongside each presentation, there was a dedicated Rocket.Chat channel<span><label for="sn-3" class="margin-toggle sidenote-number"></label><input type="checkbox" id="sn-3" class="margin-toggle"/><span class="sidenote"><a href="https://rocket.chat/">Rocket.Chat</a> seems to be an <a href="https://github.com/RocketChat/Rocket.Chat">open-source</a> alternative to Slack. Overall, the experience was great, and I appreciate the efforts of the organizers to use open source software instead of proprietary applications. I hope other conferences will do the same, and perhaps even avoid Zoom, because of recent privacy concerns (maybe try <a href="https://jitsi.org/">Jitsi</a>?).<br />
<br />
</span></span> where anyone could ask a question to the authors, or just show their appreciation for the work. This was a fantastic idea as it allowed any participant to interact with papers and authors at any time they please, which is especially important in a setting where people were spread all over the globe.</p>
<p>There were also Zoom session where authors were available for direct, face-to-face discussions, allowing for more traditional conversations. But asking questions on the channel had also the advantage of keeping a track of all questions that were asked by other people. As such, I quickly acquired the habit of watching the video, looking at the chat to see the previous discussions (even if they happened in the middle of the night in my timezone!), and then skimming the paper or asking questions myself.</p>
@ -49,11 +51,18 @@
<p>This talk was very interesting, and yet felt very familiar, as if I already saw a very similar one elsewhere. Especially for Yann LeCun, who clearly reuses the same slides for many presentations at various events. They both came back to their favourite subjects: self-supervised learning for Yann LeCun, and system 1/system 2 for Yoshua Bengio. All in all, they are very good speakers, and their presentations are always insightful. Yann LeCun gives a lot of references on recent technical advances, which is great if you want to go deeper in the approaches he recommends. Yoshua Bengio is also very good at broadening the debate around deep learning, and introducing very important concepts from cognitive science.</p>
<h2 id="prof.-michael-i.-jordan-the-decision-making-side-of-machine-learning-dynamical-statistical-and-economic-perspectives">Prof. Michael I. Jordan, <a href="https://iclr.cc/virtual_2020/speaker_8.html">The Decision-Making Side of Machine Learning: Dynamical, Statistical and Economic Perspectives</a></h2>
<p>TODO</p>
<h1 id="some-interesting-papers">Some Interesting Papers</h1>
<h2 id="natural-language-processing">Natural Language Processing</h2>
<h2 id="reinforcement-learning">Reinforcement Learning</h2>
<h2 id="ml-and-neural-network-theory">ML and Neural Network Theory</h2>
<h1 id="workshops">Workshops</h1>
<p>On Sunday, there were <a href="https://iclr.cc/virtual_2020/workshops.html">15 different workshops</a>. All of them were recorded, and are available on the website. As always, unfortunately, there are too many interesting things to watch everything, but I saw bits and pieces of different workshops.</p>
<h2 id="beyond-tabula-rasa-in-reinforcement-learning-agents-that-remember-adapt-and-generalize"><a href="https://iclr.cc/virtual_2020/workshops_12.html">Beyond ‘tabula rasa’ in reinforcement learning: agents that remember, adapt, and generalize</a></h2>
<p>A lot of pretty advanced talks about RL. The general theme was meta-learning, aka “learning to learn”. This is a very active area of research, which goes way beyond classical RL theory, and offer many interesting avenues to adjacent fields (both inside ML and outside, especially cognitive science). The <a href="http://www.betr-rl.ml/2020/abs/101/">first talk</a>, by Martha White, about inductive biases, was a very interesting and approachable introduction to the problems and challenges of the field. There was also a panel with Jürgen Schmidhuber. We hear a lot about him from the various controversies, but it’s nice to see him talking about research and future developments in RL.</p>
<h2 id="causal-learning-for-decision-making"><a href="https://iclr.cc/virtual_2020/workshops_14.html">Causal Learning For Decision Making</a></h2>
<p>Ever since I read Judea Pearl’s <a href="https://www.goodreads.com/book/show/36204378-the-book-of-why"><em>The Book of Why</em></a> on causality, I have been interested in how we can incorporate causality reasoning in machine learning. This is a complex topic, and I’m not sure yet that it is a complete revolution as Judea Pearl likes to portray it, but it nevertheless introduces a lot of new fascinating ideas. Yoshua Bengio gave an interesting talk<span><label for="sn-4" class="margin-toggle sidenote-number"></label><input type="checkbox" id="sn-4" class="margin-toggle"/><span class="sidenote">You can find it at 4:45:20 in the <a href="https://slideslive.com/38926830/workshop-on-causal-learning-for-decision-making">livestream</a> of the workshop.<br />
<br />
</span></span> (even though very similar to his keynote talk) on causal priors for deep learning.</p>
<h2 id="bridging-ai-and-cognitive-science"><a href="https://iclr.cc/virtual_2020/workshops_4.html">Bridging AI and Cognitive Science</a></h2>
<p>Cognitive science is fascinating, and I believe that collaboration between ML practitioners and cognitive scientists will greatly help advance both fields. I only watched <a href="https://baicsworkshop.github.io/program/baics_45.html">Leslie Kaelbling’s presentation</a>, which echoes a lot of things from her talk at the main conference. It complements it nicely, with more focus on intelligence, especially <em>embodied</em> intelligence. I think she has the rights approach to relationships between AI and natural science, explicitly listing the things from her work that would be helpful to natural scientists, and things she wish she knew about natural intelligences. It raises many fascinating questions on ourselves, what we build, and what we understand. I felt it was very motivational!</p>
<h2 id="integration-of-deep-neural-models-and-differential-equations"><a href="https://iclr.cc/virtual_2020/workshops_5.html">Integration of Deep Neural Models and Differential Equations</a></h2>
<p>I didn’t attend this workshop, but I think I will watch the presentations if I can find some time. I have found the intersection of differential equations and ML very interesting, ever since the famous <a href="https://papers.nips.cc/paper/7892-neural-ordinary-differential-equations">NeurIPS best paper</a> on Neural ODEs. I think that such improvements to ML theory from other fields in mathematics would be extremely beneficial to a better understanding of the systems we build.</p>
</section>
</article>
]]></summary>

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<ul>
<li>
<a href="./posts/iclr-2020-notes.html">ICLR 2020 Notes</a> - May 5, 2020
<a href="./posts/iclr-2020-notes.html">ICLR 2020 Notes: Speakers and Workshops</a> - May 5, 2020
</li>
<li>

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<h1 class="title">ICLR 2020 Notes</h1>
<h1 class="title">ICLR 2020 Notes: Speakers and Workshops</h1>
<p class="byline">May 5, 2020</p>
@ -57,7 +57,9 @@
<p>In this post, I will try to give my impressions on the event, and share the most interesting events and papers I saw.</p>
<h1 id="the-format-of-the-virtual-conference">The Format of the Virtual Conference</h1>
<p>As a result of global travel restrictions, the conference was made fully-virtual. It was supposed to take place in Addis Ababa, Ethiopia, which is great for people who are often the target of restrictive visa policies in Northern American countries.</p>
<p>The thing I appreciated most about the conference format was its emphasis on <em>asynchronous</em> communication. Given how little time they had to plan the conference, they could have made all poster presentations via video-conference and call it a day. Instead, each poster had to record a 5-minute video summarising their research. Alongside each presentation, there was a dedicated Rocket.Chat channel<span><label for="sn-2" class="margin-toggle sidenote-number"></label><input type="checkbox" id="sn-2" class="margin-toggle" /><span class="sidenote"><a href="https://rocket.chat/">Rocket.Chat</a> seems to be an <a href="https://github.com/RocketChat/Rocket.Chat">open-source</a> alternative to Slack. Overall, the experience was great, and I appreciate the efforts of the organizers to use open source software instead of proprietary applications. I hope other conferences will do the same, and perhaps even avoid Zoom, because of recent privacy concerns (maybe try <a href="https://jitsi.org/">Jitsi</a>?).<br />
<p>The thing I appreciated most about the conference format was its emphasis on <em>asynchronous</em> communication. Given how little time they had to plan the conference, they could have made all poster presentations via video-conference and call it a day. Instead, each poster had to record a 5-minute video<span><label for="sn-2" class="margin-toggle sidenote-number"></label><input type="checkbox" id="sn-2" class="margin-toggle" /><span class="sidenote">The videos are streamed using <a href="https://library.slideslive.com/">SlidesLive</a>, which is a great solution for synchronising videos and slides. It is very comfortable to navigate through the slides and synchronising the video to the slides and vice-versa. As a result, SlidesLive also has a very nice library of talks, including major conferences. This is much better than browsing YouTube randomly.<br />
<br />
</span></span> summarising their research. Alongside each presentation, there was a dedicated Rocket.Chat channel<span><label for="sn-3" class="margin-toggle sidenote-number"></label><input type="checkbox" id="sn-3" class="margin-toggle" /><span class="sidenote"><a href="https://rocket.chat/">Rocket.Chat</a> seems to be an <a href="https://github.com/RocketChat/Rocket.Chat">open-source</a> alternative to Slack. Overall, the experience was great, and I appreciate the efforts of the organizers to use open source software instead of proprietary applications. I hope other conferences will do the same, and perhaps even avoid Zoom, because of recent privacy concerns (maybe try <a href="https://jitsi.org/">Jitsi</a>?).<br />
<br />
</span></span> where anyone could ask a question to the authors, or just show their appreciation for the work. This was a fantastic idea as it allowed any participant to interact with papers and authors at any time they please, which is especially important in a setting where people were spread all over the globe.</p>
<p>There were also Zoom session where authors were available for direct, face-to-face discussions, allowing for more traditional conversations. But asking questions on the channel had also the advantage of keeping a track of all questions that were asked by other people. As such, I quickly acquired the habit of watching the video, looking at the chat to see the previous discussions (even if they happened in the middle of the night in my timezone!), and then skimming the paper or asking questions myself.</p>
@ -78,11 +80,18 @@
<p>This talk was very interesting, and yet felt very familiar, as if I already saw a very similar one elsewhere. Especially for Yann LeCun, who clearly reuses the same slides for many presentations at various events. They both came back to their favourite subjects: self-supervised learning for Yann LeCun, and system 1/system 2 for Yoshua Bengio. All in all, they are very good speakers, and their presentations are always insightful. Yann LeCun gives a lot of references on recent technical advances, which is great if you want to go deeper in the approaches he recommends. Yoshua Bengio is also very good at broadening the debate around deep learning, and introducing very important concepts from cognitive science.</p>
<h2 id="prof.-michael-i.-jordan-the-decision-making-side-of-machine-learning-dynamical-statistical-and-economic-perspectives">Prof. Michael I. Jordan, <a href="https://iclr.cc/virtual_2020/speaker_8.html">The Decision-Making Side of Machine Learning: Dynamical, Statistical and Economic Perspectives</a></h2>
<p>TODO</p>
<h1 id="some-interesting-papers">Some Interesting Papers</h1>
<h2 id="natural-language-processing">Natural Language Processing</h2>
<h2 id="reinforcement-learning">Reinforcement Learning</h2>
<h2 id="ml-and-neural-network-theory">ML and Neural Network Theory</h2>
<h1 id="workshops">Workshops</h1>
<p>On Sunday, there were <a href="https://iclr.cc/virtual_2020/workshops.html">15 different workshops</a>. All of them were recorded, and are available on the website. As always, unfortunately, there are too many interesting things to watch everything, but I saw bits and pieces of different workshops.</p>
<h2 id="beyond-tabula-rasa-in-reinforcement-learning-agents-that-remember-adapt-and-generalize"><a href="https://iclr.cc/virtual_2020/workshops_12.html">Beyond ‘tabula rasa’ in reinforcement learning: agents that remember, adapt, and generalize</a></h2>
<p>A lot of pretty advanced talks about RL. The general theme was meta-learning, aka “learning to learn”. This is a very active area of research, which goes way beyond classical RL theory, and offer many interesting avenues to adjacent fields (both inside ML and outside, especially cognitive science). The <a href="http://www.betr-rl.ml/2020/abs/101/">first talk</a>, by Martha White, about inductive biases, was a very interesting and approachable introduction to the problems and challenges of the field. There was also a panel with Jürgen Schmidhuber. We hear a lot about him from the various controversies, but it’s nice to see him talking about research and future developments in RL.</p>
<h2 id="causal-learning-for-decision-making"><a href="https://iclr.cc/virtual_2020/workshops_14.html">Causal Learning For Decision Making</a></h2>
<p>Ever since I read Judea Pearl’s <a href="https://www.goodreads.com/book/show/36204378-the-book-of-why"><em>The Book of Why</em></a> on causality, I have been interested in how we can incorporate causality reasoning in machine learning. This is a complex topic, and I’m not sure yet that it is a complete revolution as Judea Pearl likes to portray it, but it nevertheless introduces a lot of new fascinating ideas. Yoshua Bengio gave an interesting talk<span><label for="sn-4" class="margin-toggle sidenote-number"></label><input type="checkbox" id="sn-4" class="margin-toggle" /><span class="sidenote">You can find it at 4:45:20 in the <a href="https://slideslive.com/38926830/workshop-on-causal-learning-for-decision-making">livestream</a> of the workshop.<br />
<br />
</span></span> (even though very similar to his keynote talk) on causal priors for deep learning.</p>
<h2 id="bridging-ai-and-cognitive-science"><a href="https://iclr.cc/virtual_2020/workshops_4.html">Bridging AI and Cognitive Science</a></h2>
<p>Cognitive science is fascinating, and I believe that collaboration between ML practitioners and cognitive scientists will greatly help advance both fields. I only watched <a href="https://baicsworkshop.github.io/program/baics_45.html">Leslie Kaelbling’s presentation</a>, which echoes a lot of things from her talk at the main conference. It complements it nicely, with more focus on intelligence, especially <em>embodied</em> intelligence. I think she has the rights approach to relationships between AI and natural science, explicitly listing the things from her work that would be helpful to natural scientists, and things she wish she knew about natural intelligences. It raises many fascinating questions on ourselves, what we build, and what we understand. I felt it was very motivational!</p>
<h2 id="integration-of-deep-neural-models-and-differential-equations"><a href="https://iclr.cc/virtual_2020/workshops_5.html">Integration of Deep Neural Models and Differential Equations</a></h2>
<p>I didn’t attend this workshop, but I think I will watch the presentations if I can find some time. I have found the intersection of differential equations and ML very interesting, ever since the famous <a href="https://papers.nips.cc/paper/7892-neural-ordinary-differential-equations">NeurIPS best paper</a> on Neural ODEs. I think that such improvements to ML theory from other fields in mathematics would be extremely beneficial to a better understanding of the systems we build.</p>
</section>
</article>

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type="application/rss+xml" />
<lastBuildDate>Tue, 05 May 2020 00:00:00 UT</lastBuildDate>
<item>
<title>ICLR 2020 Notes</title>
<title>ICLR 2020 Notes: Speakers and Workshops</title>
<link>https://www.lozeve.com/posts/iclr-2020-notes.html</link>
<description><![CDATA[<article>
<section class="header">
@ -24,7 +24,9 @@
<p>In this post, I will try to give my impressions on the event, and share the most interesting events and papers I saw.</p>
<h1 id="the-format-of-the-virtual-conference">The Format of the Virtual Conference</h1>
<p>As a result of global travel restrictions, the conference was made fully-virtual. It was supposed to take place in Addis Ababa, Ethiopia, which is great for people who are often the target of restrictive visa policies in Northern American countries.</p>
<p>The thing I appreciated most about the conference format was its emphasis on <em>asynchronous</em> communication. Given how little time they had to plan the conference, they could have made all poster presentations via video-conference and call it a day. Instead, each poster had to record a 5-minute video summarising their research. Alongside each presentation, there was a dedicated Rocket.Chat channel<span><label for="sn-2" class="margin-toggle sidenote-number"></label><input type="checkbox" id="sn-2" class="margin-toggle"/><span class="sidenote"><a href="https://rocket.chat/">Rocket.Chat</a> seems to be an <a href="https://github.com/RocketChat/Rocket.Chat">open-source</a> alternative to Slack. Overall, the experience was great, and I appreciate the efforts of the organizers to use open source software instead of proprietary applications. I hope other conferences will do the same, and perhaps even avoid Zoom, because of recent privacy concerns (maybe try <a href="https://jitsi.org/">Jitsi</a>?).<br />
<p>The thing I appreciated most about the conference format was its emphasis on <em>asynchronous</em> communication. Given how little time they had to plan the conference, they could have made all poster presentations via video-conference and call it a day. Instead, each poster had to record a 5-minute video<span><label for="sn-2" class="margin-toggle sidenote-number"></label><input type="checkbox" id="sn-2" class="margin-toggle"/><span class="sidenote">The videos are streamed using <a href="https://library.slideslive.com/">SlidesLive</a>, which is a great solution for synchronising videos and slides. It is very comfortable to navigate through the slides and synchronising the video to the slides and vice-versa. As a result, SlidesLive also has a very nice library of talks, including major conferences. This is much better than browsing YouTube randomly.<br />
<br />
</span></span> summarising their research. Alongside each presentation, there was a dedicated Rocket.Chat channel<span><label for="sn-3" class="margin-toggle sidenote-number"></label><input type="checkbox" id="sn-3" class="margin-toggle"/><span class="sidenote"><a href="https://rocket.chat/">Rocket.Chat</a> seems to be an <a href="https://github.com/RocketChat/Rocket.Chat">open-source</a> alternative to Slack. Overall, the experience was great, and I appreciate the efforts of the organizers to use open source software instead of proprietary applications. I hope other conferences will do the same, and perhaps even avoid Zoom, because of recent privacy concerns (maybe try <a href="https://jitsi.org/">Jitsi</a>?).<br />
<br />
</span></span> where anyone could ask a question to the authors, or just show their appreciation for the work. This was a fantastic idea as it allowed any participant to interact with papers and authors at any time they please, which is especially important in a setting where people were spread all over the globe.</p>
<p>There were also Zoom session where authors were available for direct, face-to-face discussions, allowing for more traditional conversations. But asking questions on the channel had also the advantage of keeping a track of all questions that were asked by other people. As such, I quickly acquired the habit of watching the video, looking at the chat to see the previous discussions (even if they happened in the middle of the night in my timezone!), and then skimming the paper or asking questions myself.</p>
@ -45,11 +47,18 @@
<p>This talk was very interesting, and yet felt very familiar, as if I already saw a very similar one elsewhere. Especially for Yann LeCun, who clearly reuses the same slides for many presentations at various events. They both came back to their favourite subjects: self-supervised learning for Yann LeCun, and system 1/system 2 for Yoshua Bengio. All in all, they are very good speakers, and their presentations are always insightful. Yann LeCun gives a lot of references on recent technical advances, which is great if you want to go deeper in the approaches he recommends. Yoshua Bengio is also very good at broadening the debate around deep learning, and introducing very important concepts from cognitive science.</p>
<h2 id="prof.-michael-i.-jordan-the-decision-making-side-of-machine-learning-dynamical-statistical-and-economic-perspectives">Prof. Michael I. Jordan, <a href="https://iclr.cc/virtual_2020/speaker_8.html">The Decision-Making Side of Machine Learning: Dynamical, Statistical and Economic Perspectives</a></h2>
<p>TODO</p>
<h1 id="some-interesting-papers">Some Interesting Papers</h1>
<h2 id="natural-language-processing">Natural Language Processing</h2>
<h2 id="reinforcement-learning">Reinforcement Learning</h2>
<h2 id="ml-and-neural-network-theory">ML and Neural Network Theory</h2>
<h1 id="workshops">Workshops</h1>
<p>On Sunday, there were <a href="https://iclr.cc/virtual_2020/workshops.html">15 different workshops</a>. All of them were recorded, and are available on the website. As always, unfortunately, there are too many interesting things to watch everything, but I saw bits and pieces of different workshops.</p>
<h2 id="beyond-tabula-rasa-in-reinforcement-learning-agents-that-remember-adapt-and-generalize"><a href="https://iclr.cc/virtual_2020/workshops_12.html">Beyond ‘tabula rasa’ in reinforcement learning: agents that remember, adapt, and generalize</a></h2>
<p>A lot of pretty advanced talks about RL. The general theme was meta-learning, aka “learning to learn”. This is a very active area of research, which goes way beyond classical RL theory, and offer many interesting avenues to adjacent fields (both inside ML and outside, especially cognitive science). The <a href="http://www.betr-rl.ml/2020/abs/101/">first talk</a>, by Martha White, about inductive biases, was a very interesting and approachable introduction to the problems and challenges of the field. There was also a panel with Jürgen Schmidhuber. We hear a lot about him from the various controversies, but it’s nice to see him talking about research and future developments in RL.</p>
<h2 id="causal-learning-for-decision-making"><a href="https://iclr.cc/virtual_2020/workshops_14.html">Causal Learning For Decision Making</a></h2>
<p>Ever since I read Judea Pearl’s <a href="https://www.goodreads.com/book/show/36204378-the-book-of-why"><em>The Book of Why</em></a> on causality, I have been interested in how we can incorporate causality reasoning in machine learning. This is a complex topic, and I’m not sure yet that it is a complete revolution as Judea Pearl likes to portray it, but it nevertheless introduces a lot of new fascinating ideas. Yoshua Bengio gave an interesting talk<span><label for="sn-4" class="margin-toggle sidenote-number"></label><input type="checkbox" id="sn-4" class="margin-toggle"/><span class="sidenote">You can find it at 4:45:20 in the <a href="https://slideslive.com/38926830/workshop-on-causal-learning-for-decision-making">livestream</a> of the workshop.<br />
<br />
</span></span> (even though very similar to his keynote talk) on causal priors for deep learning.</p>
<h2 id="bridging-ai-and-cognitive-science"><a href="https://iclr.cc/virtual_2020/workshops_4.html">Bridging AI and Cognitive Science</a></h2>
<p>Cognitive science is fascinating, and I believe that collaboration between ML practitioners and cognitive scientists will greatly help advance both fields. I only watched <a href="https://baicsworkshop.github.io/program/baics_45.html">Leslie Kaelbling’s presentation</a>, which echoes a lot of things from her talk at the main conference. It complements it nicely, with more focus on intelligence, especially <em>embodied</em> intelligence. I think she has the rights approach to relationships between AI and natural science, explicitly listing the things from her work that would be helpful to natural scientists, and things she wish she knew about natural intelligences. It raises many fascinating questions on ourselves, what we build, and what we understand. I felt it was very motivational!</p>
<h2 id="integration-of-deep-neural-models-and-differential-equations"><a href="https://iclr.cc/virtual_2020/workshops_5.html">Integration of Deep Neural Models and Differential Equations</a></h2>
<p>I didn’t attend this workshop, but I think I will watch the presentations if I can find some time. I have found the intersection of differential equations and ML very interesting, ever since the famous <a href="https://papers.nips.cc/paper/7892-neural-ordinary-differential-equations">NeurIPS best paper</a> on Neural ODEs. I think that such improvements to ML theory from other fields in mathematics would be extremely beneficial to a better understanding of the systems we build.</p>
</section>
</article>
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posts/iclr-2020-notes.org
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@ -1,5 +1,5 @@
---
title: "ICLR 2020 Notes"
title: "ICLR 2020 Notes: Speakers and Workshops"
date: 2020-05-05
---
@ -41,7 +41,7 @@ The thing I appreciated most about the conference format was its
emphasis on /asynchronous/ communication. Given how little time they
had to plan the conference, they could have made all poster
presentations via video-conference and call it a day. Instead, each
poster had to record a 5-minute video summarising their
poster had to record a 5-minute video[fn:slideslive] summarising their
research. Alongside each presentation, there was a dedicated
Rocket.Chat channel[fn:rocketchat] where anyone could ask a question
to the authors, or just show their appreciation for the work. This was
@ -62,6 +62,13 @@ All of these excellent ideas were implemented by an [[https://iclr.cc/virtual_20
collecting all papers in a searchable, easy-to-use interface, and even
a nice [[https://iclr.cc/virtual_2020/paper_vis.html][visualisation]] of papers as a point cloud!
[fn:slideslive] The videos are streamed using [[https://library.slideslive.com/][SlidesLive]], which is a
great solution for synchronising videos and slides. It is very
comfortable to navigate through the slides and synchronising the video
to the slides and vice-versa. As a result, SlidesLive also has a very
nice library of talks, including major conferences. This is much
better than browsing YouTube randomly.
[fn:rocketchat] [[https://rocket.chat/][Rocket.Chat]] seems to be an [[https://github.com/RocketChat/Rocket.Chat][open-source]] alternative to
Slack. Overall, the experience was great, and I appreciate the efforts
of the organizers to use open source software instead of proprietary
@ -135,12 +142,59 @@ very important concepts from cognitive science.
TODO
* Some Interesting Papers
** Natural Language Processing
** Reinforcement Learning
** ML and Neural Network Theory
* Workshops
On Sunday, there were [[https://iclr.cc/virtual_2020/workshops.html][15 different workshops]]. All of them were
recorded, and are available on the website. As always, unfortunately,
there are too many interesting things to watch everything, but I saw
bits and pieces of different workshops.
** [[https://iclr.cc/virtual_2020/workshops_12.html][Beyond 'tabula rasa' in reinforcement learning: agents that remember, adapt, and generalize]]
A lot of pretty advanced talks about RL. The general theme was
meta-learning, aka "learning to learn". This is a very active area of
research, which goes way beyond classical RL theory, and offer many
interesting avenues to adjacent fields (both inside ML and outside,
especially cognitive science). The [[http://www.betr-rl.ml/2020/abs/101/][first talk]], by Martha White, about
inductive biases, was a very interesting and approachable introduction
to the problems and challenges of the field. There was also a panel
with Jürgen Schmidhuber. We hear a lot about him from the various
controversies, but it's nice to see him talking about research and
future developments in RL.
** [[https://iclr.cc/virtual_2020/workshops_14.html][Causal Learning For Decision Making]]
Ever since I read Judea Pearl's [[https://www.goodreads.com/book/show/36204378-the-book-of-why][/The Book of Why/]] on causality, I have
been interested in how we can incorporate causality reasoning in
machine learning. This is a complex topic, and I'm not sure yet that
it is a complete revolution as Judea Pearl likes to portray it, but it
nevertheless introduces a lot of new fascinating ideas. Yoshua Bengio
gave an interesting talk[fn:bengioworkshop] (even though very similar
to his keynote talk) on causal priors for deep learning.
[fn:bengioworkshop] You can find it at 4:45:20 in the [[https://slideslive.com/38926830/workshop-on-causal-learning-for-decision-making][livestream]] of
the workshop.
** [[https://iclr.cc/virtual_2020/workshops_4.html][Bridging AI and Cognitive Science]]
Cognitive science is fascinating, and I believe that collaboration
between ML practitioners and cognitive scientists will greatly help
advance both fields. I only watched [[https://baicsworkshop.github.io/program/baics_45.html][Leslie Kaelbling's presentation]],
which echoes a lot of things from her talk at the main conference. It
complements it nicely, with more focus on intelligence, especially
/embodied/ intelligence. I think she has the rights approach to
relationships between AI and natural science, explicitly listing the
things from her work that would be helpful to natural scientists, and
things she wish she knew about natural intelligences. It raises many
fascinating questions on ourselves, what we build, and what we
understand. I felt it was very motivational!
** [[https://iclr.cc/virtual_2020/workshops_5.html][Integration of Deep Neural Models and Differential Equations]]
I didn't attend this workshop, but I think I will watch the
presentations if I can find some time. I have found the intersection
of differential equations and ML very interesting, ever since the
famous [[https://papers.nips.cc/paper/7892-neural-ordinary-differential-equations][NeurIPS best paper]] on Neural ODEs. I think that such
improvements to ML theory from other fields in mathematics would be
extremely beneficial to a better understanding of the systems we
build.