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</head> </head>
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<a href="./">Home</a> <a href="./">Home</a>
<a href="./archive.html">Posts</a>
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<a href="./archive.html">Archive</a>
<a href="./contact.html">Contact</a> <a href="./contact.html">Contact</a>
</nav> </nav>
<h1 class="title">Archives</h1> <h1 class="title">Archives</h1>
</header> </header>
</article>
<p>Here you can find all my previous posts:</p> <p>Here you can find all my previous posts:</p>
<ul> <ul>
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<id>https://www.lozeve.com/posts/dyalog-apl-competition-2020-phase-2.html</id> <id>https://www.lozeve.com/posts/dyalog-apl-competition-2020-phase-2.html</id>
<published>2020-08-02T00:00:00Z</published> <published>2020-08-02T00:00:00Z</published>
<updated>2020-08-02T00:00:00Z</updated> <updated>2020-08-02T00:00:00Z</updated>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction">Introduction</a></li> <li><a href="#introduction">Introduction</a></li>
<li><a href="#problem-1-take-a-dive">Problem 1 – Take a Dive</a></li> <li><a href="#problem-1-take-a-dive">Problem 1 – Take a Dive</a></li>
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<div class="sourceCode" id="cb21"><pre class="sourceCode default"><code class="sourceCode default"><span id="cb21-1"><a href="#cb21-1" aria-hidden="true"></a> :EndNamespace</span> <div class="sourceCode" id="cb21"><pre class="sourceCode default"><code class="sourceCode default"><span id="cb21-1"><a href="#cb21-1" aria-hidden="true"></a> :EndNamespace</span>
<span id="cb21-2"><a href="#cb21-2" aria-hidden="true"></a>:EndNamespace</span></code></pre></div> <span id="cb21-2"><a href="#cb21-2" aria-hidden="true"></a>:EndNamespace</span></code></pre></div>
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<id>https://www.lozeve.com/posts/dyalog-apl-competition-2020-phase-1.html</id> <id>https://www.lozeve.com/posts/dyalog-apl-competition-2020-phase-1.html</id>
<published>2020-08-02T00:00:00Z</published> <published>2020-08-02T00:00:00Z</published>
<updated>2020-08-02T00:00:00Z</updated> <updated>2020-08-02T00:00:00Z</updated>
<summary type="html"><![CDATA[<article> <summary type="html"><![CDATA[<section>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction">Introduction</a></li> <li><a href="#introduction">Introduction</a></li>
<li><a href="#lets-split">1. Let’s Split!</a></li> <li><a href="#lets-split">1. Let’s Split!</a></li>
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<span id="cb6-12"><a href="#cb6-12" aria-hidden="true"></a> ─────────────────────────────────────────────────────────────┘</span></code></pre></div> <span id="cb6-12"><a href="#cb6-12" aria-hidden="true"></a> ─────────────────────────────────────────────────────────────┘</span></code></pre></div>
<p>Next, we clean this up with Ravel (<code>,</code>) and we can Mix to obtain the final result.</p> <p>Next, we clean this up with Ravel (<code>,</code>) and we can Mix to obtain the final result.</p>
</section> </section>
</article>
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<entry> <entry>
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<id>https://www.lozeve.com/posts/operations-research-references.html</id> <id>https://www.lozeve.com/posts/operations-research-references.html</id>
<published>2020-05-27T00:00:00Z</published> <published>2020-05-27T00:00:00Z</published>
<updated>2020-05-27T00:00:00Z</updated> <updated>2020-05-27T00:00:00Z</updated>
<summary type="html"><![CDATA[<article> <summary type="html"><![CDATA[<section>
<section class="header">
</section>
<section>
<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction">Introduction</a></li> <li><a href="#introduction">Introduction</a></li>
<li><a href="#why-is-it-hard-to-approach">Why is it hard to approach?</a></li> <li><a href="#why-is-it-hard-to-approach">Why is it hard to approach?</a></li>
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<id>https://www.lozeve.com/posts/iclr-2020-notes.html</id> <id>https://www.lozeve.com/posts/iclr-2020-notes.html</id>
<published>2020-05-05T00:00:00Z</published> <published>2020-05-05T00:00:00Z</published>
<updated>2020-05-05T00:00:00Z</updated> <updated>2020-05-05T00:00:00Z</updated>
<summary type="html"><![CDATA[<article> <summary type="html"><![CDATA[<section>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#the-format-of-the-virtual-conference">The Format of the Virtual Conference</a></li> <li><a href="#the-format-of-the-virtual-conference">The Format of the Virtual Conference</a></li>
<li><a href="#speakers">Speakers</a> <li><a href="#speakers">Speakers</a>
@ -597,7 +578,6 @@
<h3 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></h3> <h3 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></h3>
<p>I didn’t attend this workshop, but I think I will watch the presentations if I can find the 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> <p>I didn’t attend this workshop, but I think I will watch the presentations if I can find the 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> </section>
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<entry> <entry>
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<id>https://www.lozeve.com/posts/hierarchical-optimal-transport-for-document-classification.html</id> <id>https://www.lozeve.com/posts/hierarchical-optimal-transport-for-document-classification.html</id>
<published>2020-04-05T00:00:00Z</published> <published>2020-04-05T00:00:00Z</published>
<updated>2020-04-05T00:00:00Z</updated> <updated>2020-04-05T00:00:00Z</updated>
<summary type="html"><![CDATA[<article> <summary type="html"><![CDATA[<section>
<section class="header">
</section>
<section>
<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction-and-motivation">Introduction and motivation</a></li> <li><a href="#introduction-and-motivation">Introduction and motivation</a></li>
<li><a href="#background-optimal-transport">Background: optimal transport</a></li> <li><a href="#background-optimal-transport">Background: optimal transport</a></li>
@ -698,7 +674,6 @@ W_1(p, q) = \min_{P \in \mathbb{R}_+^{n\times m}} \sum_{i,j} C_{i,j} P_{i,j}
</div> </div>
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</section> </section>
</article>
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</entry> </entry>
<entry> <entry>
@ -707,11 +682,7 @@ W_1(p, q) = \min_{P \in \mathbb{R}_+^{n\times m}} \sum_{i,j} C_{i,j} P_{i,j}
<id>https://www.lozeve.com/posts/self-learning-chatbots-destygo.html</id> <id>https://www.lozeve.com/posts/self-learning-chatbots-destygo.html</id>
<published>2019-04-06T00:00:00Z</published> <published>2019-04-06T00:00:00Z</published>
<updated>2019-04-06T00:00:00Z</updated> <updated>2019-04-06T00:00:00Z</updated>
<summary type="html"><![CDATA[<article> <summary type="html"><![CDATA[<section>
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<p>Last week I made a presentation at the <a href="https://www.meetup.com/Paris-NLP/">Paris NLP Meetup</a>, on how we implemented self-learning chatbots in production at Mindsay.</p> <p>Last week I made a presentation at the <a href="https://www.meetup.com/Paris-NLP/">Paris NLP Meetup</a>, on how we implemented self-learning chatbots in production at Mindsay.</p>
<p>It was fascinating to other people interested in NLP about the technologies and models we deploy at work! It’s always nice to have some feedback about our work, and preparing this talk forced me to take a step back about what we do and rethink it in new interesting ways.</p> <p>It was fascinating to other people interested in NLP about the technologies and models we deploy at work! It’s always nice to have some feedback about our work, and preparing this talk forced me to take a step back about what we do and rethink it in new interesting ways.</p>
<p>Also check out the <a href="https://nlpparis.wordpress.com/2019/03/29/paris-nlp-season-3-meetup-4-at-meilleursagents/">other presentations</a>, one about diachronic (i.e. time-dependent) word embeddings and the other about the different models and the use of Knowledge Bases for Information Retrieval. (This might even give us new ideas to explore…)</p> <p>Also check out the <a href="https://nlpparis.wordpress.com/2019/03/29/paris-nlp-season-3-meetup-4-at-meilleursagents/">other presentations</a>, one about diachronic (i.e. time-dependent) word embeddings and the other about the different models and the use of Knowledge Bases for Information Retrieval. (This might even give us new ideas to explore…)</p>
@ -719,7 +690,6 @@ W_1(p, q) = \min_{P \in \mathbb{R}_+^{n\times m}} \sum_{i,j} C_{i,j} P_{i,j}
<p><strong><strong>Update:</strong></strong> The videos are now available on the <a href="https://nlpparis.wordpress.com/2019/03/29/paris-nlp-season-3-meetup-4-at-meilleursagents/">NLP Meetup website</a>.</p> <p><strong><strong>Update:</strong></strong> The videos are now available on the <a href="https://nlpparis.wordpress.com/2019/03/29/paris-nlp-season-3-meetup-4-at-meilleursagents/">NLP Meetup website</a>.</p>
<p><strong><strong>Update 2:</strong></strong> Destygo changed its name to <a href="https://www.mindsay.com/">Mindsay</a>!</p> <p><strong><strong>Update 2:</strong></strong> Destygo changed its name to <a href="https://www.mindsay.com/">Mindsay</a>!</p>
</section> </section>
</article>
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</entry> </entry>
<entry> <entry>
@ -728,11 +698,7 @@ W_1(p, q) = \min_{P \in \mathbb{R}_+^{n\times m}} \sum_{i,j} C_{i,j} P_{i,j}
<id>https://www.lozeve.com/posts/ginibre-ensemble.html</id> <id>https://www.lozeve.com/posts/ginibre-ensemble.html</id>
<published>2019-03-20T00:00:00Z</published> <published>2019-03-20T00:00:00Z</published>
<updated>2019-03-20T00:00:00Z</updated> <updated>2019-03-20T00:00:00Z</updated>
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<h3 id="ginibre-ensemble-and-its-properties">Ginibre ensemble and its properties</h3> <h3 id="ginibre-ensemble-and-its-properties">Ginibre ensemble and its properties</h3>
<p>The <em>Ginibre ensemble</em> is a set of random matrices with the entries chosen independently. Each entry of a <span class="math inline">\(n \times n\)</span> matrix is a complex number, with both the real and imaginary part sampled from a normal distribution of mean zero and variance <span class="math inline">\(1/2n\)</span>.</p> <p>The <em>Ginibre ensemble</em> is a set of random matrices with the entries chosen independently. Each entry of a <span class="math inline">\(n \times n\)</span> matrix is a complex number, with both the real and imaginary part sampled from a normal distribution of mean zero and variance <span class="math inline">\(1/2n\)</span>.</p>
<p>Random matrices distributions are very complex and are a very active subject of research. I stumbled on this example while reading an article in <em>Notices of the AMS</em> by Brian C. Hall <a href="#ref-1">(1)</a>.</p> <p>Random matrices distributions are very complex and are a very active subject of research. I stumbled on this example while reading an article in <em>Notices of the AMS</em> by Brian C. Hall <a href="#ref-1">(1)</a>.</p>
@ -759,7 +725,6 @@ W_1(p, q) = \min_{P \in \mathbb{R}_+^{n\times m}} \sum_{i,j} C_{i,j} P_{i,j}
<li><span id="ref-2"></span>Ginibre, Jean. “Statistical ensembles of complex, quaternion, and real matrices.” Journal of Mathematical Physics 6.3 (1965): 440-449. <a href="https://doi.org/10.1063/1.1704292">https://doi.org/10.1063/1.1704292</a></li> <li><span id="ref-2"></span>Ginibre, Jean. “Statistical ensembles of complex, quaternion, and real matrices.” Journal of Mathematical Physics 6.3 (1965): 440-449. <a href="https://doi.org/10.1063/1.1704292">https://doi.org/10.1063/1.1704292</a></li>
</ol> </ol>
</section> </section>
</article>
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</entry> </entry>
<entry> <entry>
@ -768,11 +733,7 @@ W_1(p, q) = \min_{P \in \mathbb{R}_+^{n\times m}} \sum_{i,j} C_{i,j} P_{i,j}
<id>https://www.lozeve.com/posts/peano.html</id> <id>https://www.lozeve.com/posts/peano.html</id>
<published>2019-03-18T00:00:00Z</published> <published>2019-03-18T00:00:00Z</published>
<updated>2019-03-18T00:00:00Z</updated> <updated>2019-03-18T00:00:00Z</updated>
<summary type="html"><![CDATA[<article> <summary type="html"><![CDATA[<section>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction">Introduction</a></li> <li><a href="#introduction">Introduction</a></li>
<li><a href="#the-axioms">The Axioms</a></li> <li><a href="#the-axioms">The Axioms</a></li>
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@ -904,11 +864,7 @@ then <span class="math inline">\(\varphi(n)\)</span> is true for every natural n
<id>https://www.lozeve.com/posts/reinforcement-learning-1.html</id> <id>https://www.lozeve.com/posts/reinforcement-learning-1.html</id>
<published>2018-11-21T00:00:00Z</published> <published>2018-11-21T00:00:00Z</published>
<updated>2018-11-21T00:00:00Z</updated> <updated>2018-11-21T00:00:00Z</updated>
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<h2 id="introduction">Introduction</h2> <h2 id="introduction">Introduction</h2>
<p>In this series of blog posts, I intend to write my notes as I go through Richard S. Sutton’s excellent <em>Reinforcement Learning: An Introduction</em> <a href="#ref-1">(1)</a>.</p> <p>In this series of blog posts, I intend to write my notes as I go through Richard S. Sutton’s excellent <em>Reinforcement Learning: An Introduction</em> <a href="#ref-1">(1)</a>.</p>
<p>I will try to formalise the maths behind it a little bit, mainly because I would like to use it as a useful personal reference to the main concepts in RL. I will probably add a few remarks about a possible implementation as I go on.</p> <p>I will try to formalise the maths behind it a little bit, mainly because I would like to use it as a useful personal reference to the main concepts in RL. I will probably add a few remarks about a possible implementation as I go on.</p>
@ -998,7 +954,6 @@ q_{\pi}(s,a) &amp;= \mathbb{E}_{\pi}\left[ \sum_{k=0}^{\infty} \gamma^k R_{t+k+1
<li><span id="ref-1"></span>R. S. Sutton and A. G. Barto, Reinforcement learning: an introduction, Second edition. Cambridge, MA: The MIT Press, 2018.</li> <li><span id="ref-1"></span>R. S. Sutton and A. G. Barto, Reinforcement learning: an introduction, Second edition. Cambridge, MA: The MIT Press, 2018.</li>
</ol> </ol>
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@ -1007,11 +962,7 @@ q_{\pi}(s,a) &amp;= \mathbb{E}_{\pi}\left[ \sum_{k=0}^{\infty} \gamma^k R_{t+k+1
<id>https://www.lozeve.com/posts/ising-apl.html</id> <id>https://www.lozeve.com/posts/ising-apl.html</id>
<published>2018-03-05T00:00:00Z</published> <published>2018-03-05T00:00:00Z</published>
<updated>2018-03-05T00:00:00Z</updated> <updated>2018-03-05T00:00:00Z</updated>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#the-apl-family-of-languages">The APL family of languages</a> <li><a href="#the-apl-family-of-languages">The APL family of languages</a>
<ul> <ul>
@ -1211,7 +1162,6 @@ q_{\pi}(s,a) &amp;= \mathbb{E}_{\pi}\left[ \sum_{k=0}^{\infty} \gamma^k R_{t+k+1
<p>It took me some time to write this, but Dyalog’s tools make it really easy to insert symbols and to look up what they do. Next time, I will look into some ASCII-based APL descendants. J seems to have a <a href="http://code.jsoftware.com/wiki/NuVoc">good documentation</a> and a tradition of <em>tacit definitions</em>, similar to the point-free style in Haskell. Overall, J seems well-suited to modern functional programming, while APL is still under the influence of its early days when it was more procedural. Another interesting area is K, Q, and their database engine kdb+, which seems to be extremely performant and actually used in production.</p> <p>It took me some time to write this, but Dyalog’s tools make it really easy to insert symbols and to look up what they do. Next time, I will look into some ASCII-based APL descendants. J seems to have a <a href="http://code.jsoftware.com/wiki/NuVoc">good documentation</a> and a tradition of <em>tacit definitions</em>, similar to the point-free style in Haskell. Overall, J seems well-suited to modern functional programming, while APL is still under the influence of its early days when it was more procedural. Another interesting area is K, Q, and their database engine kdb+, which seems to be extremely performant and actually used in production.</p>
<p>Still, Unicode symbols make the code much more readable, mainly because there is a one-to-one link between symbols and functions, which cannot be maintained with only a few ASCII characters.</p> <p>Still, Unicode symbols make the code much more readable, mainly because there is a one-to-one link between symbols and functions, which cannot be maintained with only a few ASCII characters.</p>
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<a href="./">Home</a> <a href="./">Home</a>
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<a href="./archive.html">Archive</a>
<a href="./contact.html">Contact</a> <a href="./contact.html">Contact</a>
</nav> </nav>
<h1 class="title">Contact</h1> <h1 class="title">Contact</h1>
</header> </header>
</article>
<dl> <dl>
<dt><strong><a href="https://jedisct1.github.io/minisign/">minisign</a> public key</strong></dt> <dt><strong><a href="https://jedisct1.github.io/minisign/">minisign</a> public key</strong></dt>
<dd>RWQ6uexORp8f7USHA7nX9lFfltaCA9x6aBV06MvgiGjUt6BVf6McyD26 <dd>RWQ6uexORp8f7USHA7nX9lFfltaCA9x6aBV06MvgiGjUt6BVf6McyD26
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<h1 class="title">Curriculum Vitæ</h1> <h1 class="title">Curriculum Vitæ</h1>
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<p><a href="./files/cv.pdf">(PDF version)</a></p> <p><a href="./files/cv.pdf">(PDF version)</a></p>
<h2 id="work-experience">Work experience</h2> <h2 id="work-experience">Work experience</h2>
<h4 id="mindsay-rd-data-scientist-and-engineering-manager"><a href="https://www.mindsay.com/">Mindsay</a>: R&amp;D Data Scientist and Engineering Manager</h4> <h4 id="mindsay-rd-data-scientist-and-engineering-manager"><a href="https://www.mindsay.com/">Mindsay</a>: R&amp;D Data Scientist and Engineering Manager</h4>
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<p><strong>Fencing:</strong> vice-president of the 2016 <a href="http://x-systra.com/">X-SYSTRA International Fencing Challenge</a>; 29th in the 2016 sabre French Student Championships</p> <p><strong>Fencing:</strong> vice-president of the 2016 <a href="http://x-systra.com/">X-SYSTRA International Fencing Challenge</a>; 29th in the 2016 sabre French Student Championships</p>
<p><strong>Scuba-diving:</strong> CMAS ★ ★ ★, 170+ dives</p> <p><strong>Scuba-diving:</strong> CMAS ★ ★ ★, 170+ dives</p>
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<h1 class="title">Home</h1>
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<p>Hi! I am a Data Scientist <p>Hi! I am a Data Scientist
@ -133,6 +131,8 @@ public key: RWQ6uexORp8f7USHA7nX9lFfltaCA9x6aBV06MvgiGjUt6BVf6McyD26
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<h1 class="title">Dyalog APL Problem Solving Competition 2020 — Phase I</h1> <h1 class="title">Dyalog APL Problem Solving Competition 2020 — Phase I</h1>
<p class="subtitle">Annotated Solutions</p> <p class="subtitle">Annotated Solutions</p>
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<p class="byline">August 2, 2020</p> <p class="byline">August 2, 2020</p>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction">Introduction</a></li> <li><a href="#introduction">Introduction</a></li>
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<span id="cb6-12"><a href="#cb6-12" aria-hidden="true"></a> ─────────────────────────────────────────────────────────────┘</span></code></pre></div> <span id="cb6-12"><a href="#cb6-12" aria-hidden="true"></a> ─────────────────────────────────────────────────────────────┘</span></code></pre></div>
<p>Next, we clean this up with Ravel (<code>,</code>) and we can Mix to obtain the final result.</p> <p>Next, we clean this up with Ravel (<code>,</code>) and we can Mix to obtain the final result.</p>
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<h1 class="title">Dyalog APL Problem Solving Competition 2020 — Phase II</h1> <h1 class="title">Dyalog APL Problem Solving Competition 2020 — Phase II</h1>
<p class="subtitle">Annotated Solutions</p> <p class="subtitle">Annotated Solutions</p>
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<p class="byline">August 2, 2020</p> <p class="byline">August 2, 2020</p>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction">Introduction</a></li> <li><a href="#introduction">Introduction</a></li>
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<div class="sourceCode" id="cb21"><pre class="sourceCode default"><code class="sourceCode default"><span id="cb21-1"><a href="#cb21-1" aria-hidden="true"></a> :EndNamespace</span> <div class="sourceCode" id="cb21"><pre class="sourceCode default"><code class="sourceCode default"><span id="cb21-1"><a href="#cb21-1" aria-hidden="true"></a> :EndNamespace</span>
<span id="cb21-2"><a href="#cb21-2" aria-hidden="true"></a>:EndNamespace</span></code></pre></div> <span id="cb21-2"><a href="#cb21-2" aria-hidden="true"></a>:EndNamespace</span></code></pre></div>
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<h1 class="title">Random matrices from the Ginibre ensemble</h1> <h1 class="title">Random matrices from the Ginibre ensemble</h1>
<p class="byline">March 20, 2019</p> <p class="byline">March 20, 2019</p>
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<h3 id="ginibre-ensemble-and-its-properties">Ginibre ensemble and its properties</h3> <h3 id="ginibre-ensemble-and-its-properties">Ginibre ensemble and its properties</h3>
<p>The <em>Ginibre ensemble</em> is a set of random matrices with the entries chosen independently. Each entry of a <span class="math inline">\(n \times n\)</span> matrix is a complex number, with both the real and imaginary part sampled from a normal distribution of mean zero and variance <span class="math inline">\(1/2n\)</span>.</p> <p>The <em>Ginibre ensemble</em> is a set of random matrices with the entries chosen independently. Each entry of a <span class="math inline">\(n \times n\)</span> matrix is a complex number, with both the real and imaginary part sampled from a normal distribution of mean zero and variance <span class="math inline">\(1/2n\)</span>.</p>
@ -71,9 +65,10 @@
<li><span id="ref-2"></span>Ginibre, Jean. “Statistical ensembles of complex, quaternion, and real matrices.” Journal of Mathematical Physics 6.3 (1965): 440-449. <a href="https://doi.org/10.1063/1.1704292">https://doi.org/10.1063/1.1704292</a></li> <li><span id="ref-2"></span>Ginibre, Jean. “Statistical ensembles of complex, quaternion, and real matrices.” Journal of Mathematical Physics 6.3 (1965): 440-449. <a href="https://doi.org/10.1063/1.1704292">https://doi.org/10.1063/1.1704292</a></li>
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<h1 class="title">Reading notes: Hierarchical Optimal Transport for Document Representation</h1> <h1 class="title">Reading notes: Hierarchical Optimal Transport for Document Representation</h1>
<p class="byline">April 5, 2020</p> <p class="byline">April 5, 2020</p>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction-and-motivation">Introduction and motivation</a></li> <li><a href="#introduction-and-motivation">Introduction and motivation</a></li>
@ -132,9 +126,10 @@ W_1(p, q) = \min_{P \in \mathbb{R}_+^{n\times m}} \sum_{i,j} C_{i,j} P_{i,j}
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<h1 class="title">ICLR 2020 Notes: Speakers and Workshops</h1> <h1 class="title">ICLR 2020 Notes: Speakers and Workshops</h1>
<p class="byline">May 5, 2020</p> <p class="byline">May 5, 2020</p>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#the-format-of-the-virtual-conference">The Format of the Virtual Conference</a></li> <li><a href="#the-format-of-the-virtual-conference">The Format of the Virtual Conference</a></li>
@ -103,9 +97,10 @@
<h3 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></h3> <h3 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></h3>
<p>I didn’t attend this workshop, but I think I will watch the presentations if I can find the 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> <p>I didn’t attend this workshop, but I think I will watch the presentations if I can find the 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>
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<h1 class="title">Ising model simulation in APL</h1> <h1 class="title">Ising model simulation in APL</h1>
<p class="byline">March 5, 2018</p> <p class="byline">March 5, 2018</p>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#the-apl-family-of-languages">The APL family of languages</a> <li><a href="#the-apl-family-of-languages">The APL family of languages</a>
@ -244,9 +238,10 @@
<p>It took me some time to write this, but Dyalog’s tools make it really easy to insert symbols and to look up what they do. Next time, I will look into some ASCII-based APL descendants. J seems to have a <a href="http://code.jsoftware.com/wiki/NuVoc">good documentation</a> and a tradition of <em>tacit definitions</em>, similar to the point-free style in Haskell. Overall, J seems well-suited to modern functional programming, while APL is still under the influence of its early days when it was more procedural. Another interesting area is K, Q, and their database engine kdb+, which seems to be extremely performant and actually used in production.</p> <p>It took me some time to write this, but Dyalog’s tools make it really easy to insert symbols and to look up what they do. Next time, I will look into some ASCII-based APL descendants. J seems to have a <a href="http://code.jsoftware.com/wiki/NuVoc">good documentation</a> and a tradition of <em>tacit definitions</em>, similar to the point-free style in Haskell. Overall, J seems well-suited to modern functional programming, while APL is still under the influence of its early days when it was more procedural. Another interesting area is K, Q, and their database engine kdb+, which seems to be extremely performant and actually used in production.</p>
<p>Still, Unicode symbols make the code much more readable, mainly because there is a one-to-one link between symbols and functions, which cannot be maintained with only a few ASCII characters.</p> <p>Still, Unicode symbols make the code much more readable, mainly because there is a one-to-one link between symbols and functions, which cannot be maintained with only a few ASCII characters.</p>
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<h1 class="title">Ising model simulation</h1> <h1 class="title">Ising model simulation</h1>
<p class="byline">February 5, 2018 &ndash; Dimitri Lozeve</p> <p class="byline">February 5, 2018 &ndash; Dimitri Lozeve</p>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#mathematical-definition">Mathematical definition</a></li> <li><a href="#mathematical-definition">Mathematical definition</a></li>
@ -157,9 +149,10 @@ J\sigma_i \sum_{j\sim i} \sigma_j. \]</span></p>
<h2 id="conclusion">Conclusion</h2> <h2 id="conclusion">Conclusion</h2>
<p>The Ising model is a really easy (and common) example use of MCMC and Metropolis-Hastings. It allows to easily and intuitively understand how the algorithm works, and to make nice visualizations!</p> <p>The Ising model is a really easy (and common) example use of MCMC and Metropolis-Hastings. It allows to easily and intuitively understand how the algorithm works, and to make nice visualizations!</p>
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<h1 class="title">Generating and representing L-systems</h1> <h1 class="title">Generating and representing L-systems</h1>
<p class="byline">January 18, 2018 &ndash; Dimitri Lozeve</p> <p class="byline">January 18, 2018 &ndash; Dimitri Lozeve</p>
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<li><a href="#what-is-an-l-system">What is an L-system?</a> <li><a href="#what-is-an-l-system">What is an L-system?</a>
@ -183,9 +175,10 @@ Available options:
<li>Corte, Leo. “L-systems and Penrose P3 in Inkscape.” <em>The Brick in the Sky.</em> <a href="https://thebrickinthesky.wordpress.com/2013/03/17/l-systems-and-penrose-p3-in-inkscape/">https://thebrickinthesky.wordpress.com/2013/03/17/l-systems-and-penrose-p3-in-inkscape/</a></li> <li>Corte, Leo. “L-systems and Penrose P3 in Inkscape.” <em>The Brick in the Sky.</em> <a href="https://thebrickinthesky.wordpress.com/2013/03/17/l-systems-and-penrose-p3-in-inkscape/">https://thebrickinthesky.wordpress.com/2013/03/17/l-systems-and-penrose-p3-in-inkscape/</a></li>
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<h1 class="title">Operations Research and Optimization: where to start?</h1> <h1 class="title">Operations Research and Optimization: where to start?</h1>
<p class="byline">May 27, 2020</p> <p class="byline">May 27, 2020</p>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction">Introduction</a></li> <li><a href="#introduction">Introduction</a></li>
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<h1 class="title">Peano Axioms</h1> <h1 class="title">Peano Axioms</h1>
<p class="byline">March 18, 2019</p> <p class="byline">March 18, 2019</p>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction">Introduction</a></li> <li><a href="#introduction">Introduction</a></li>
@ -167,9 +161,10 @@ then <span class="math inline">\(\varphi(n)\)</span> is true for every natural n
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<h1 class="title">Quick Notes on Reinforcement Learning</h1> <h1 class="title">Quick Notes on Reinforcement Learning</h1>
<p class="byline">November 21, 2018</p> <p class="byline">November 21, 2018</p>
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<h2 id="introduction">Introduction</h2> <h2 id="introduction">Introduction</h2>
<p>In this series of blog posts, I intend to write my notes as I go through Richard S. Sutton’s excellent <em>Reinforcement Learning: An Introduction</em> <a href="#ref-1">(1)</a>.</p> <p>In this series of blog posts, I intend to write my notes as I go through Richard S. Sutton’s excellent <em>Reinforcement Learning: An Introduction</em> <a href="#ref-1">(1)</a>.</p>
@ -134,9 +128,10 @@ q_{\pi}(s,a) &amp;= \mathbb{E}_{\pi}\left[ \sum_{k=0}^{\infty} \gamma^k R_{t+k+1
<li><span id="ref-1"></span>R. S. Sutton and A. G. Barto, Reinforcement learning: an introduction, Second edition. Cambridge, MA: The MIT Press, 2018.</li> <li><span id="ref-1"></span>R. S. Sutton and A. G. Barto, Reinforcement learning: an introduction, Second edition. Cambridge, MA: The MIT Press, 2018.</li>
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<h1 class="title">Mindsay: Towards Self-Learning Chatbots</h1> <h1 class="title">Mindsay: Towards Self-Learning Chatbots</h1>
<p class="byline">April 6, 2019</p> <p class="byline">April 6, 2019</p>
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<p>Last week I made a presentation at the <a href="https://www.meetup.com/Paris-NLP/">Paris NLP Meetup</a>, on how we implemented self-learning chatbots in production at Mindsay.</p> <p>Last week I made a presentation at the <a href="https://www.meetup.com/Paris-NLP/">Paris NLP Meetup</a>, on how we implemented self-learning chatbots in production at Mindsay.</p>
<p>It was fascinating to other people interested in NLP about the technologies and models we deploy at work! It’s always nice to have some feedback about our work, and preparing this talk forced me to take a step back about what we do and rethink it in new interesting ways.</p> <p>It was fascinating to other people interested in NLP about the technologies and models we deploy at work! It’s always nice to have some feedback about our work, and preparing this talk forced me to take a step back about what we do and rethink it in new interesting ways.</p>
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<p><strong><strong>Update:</strong></strong> The videos are now available on the <a href="https://nlpparis.wordpress.com/2019/03/29/paris-nlp-season-3-meetup-4-at-meilleursagents/">NLP Meetup website</a>.</p> <p><strong><strong>Update:</strong></strong> The videos are now available on the <a href="https://nlpparis.wordpress.com/2019/03/29/paris-nlp-season-3-meetup-4-at-meilleursagents/">NLP Meetup website</a>.</p>
<p><strong><strong>Update 2:</strong></strong> Destygo changed its name to <a href="https://www.mindsay.com/">Mindsay</a>!</p> <p><strong><strong>Update 2:</strong></strong> Destygo changed its name to <a href="https://www.mindsay.com/">Mindsay</a>!</p>
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<h2><a href="./files/tdanetworks.pdf">Topological Data Analysis of time-dependent networks</a></h2> <h2><a href="./files/tdanetworks.pdf">Topological Data Analysis of time-dependent networks</a></h2>
<p>Application of the recent advances in Topological Data Analysis (TDA) and Persistent Homology to periodicity detection in temporal networks. <a href="./files/tdanetworks.pdf">Master's thesis dissertation.</a></p> <p>Application of the recent advances in Topological Data Analysis (TDA) and Persistent Homology to periodicity detection in temporal networks. <a href="./files/tdanetworks.pdf">Master's thesis dissertation.</a></p>
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<h1 class="title">ADS-B data visualization</h1> <h1 class="title">ADS-B data visualization</h1>
<p class="byline">July 26, 2017</p> <p class="byline">July 26, 2017</p>
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<h1 class="title">Civilisation</h1> <h1 class="title">Civilisation</h1>
<p class="byline">July 26, 2017</p> <p class="byline">July 26, 2017</p>
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<h1 class="title">Community Detection</h1> <h1 class="title">Community Detection</h1>
<p class="byline">July 26, 2017</p> <p class="byline">July 26, 2017</p>
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<h1 class="title">Ising model simulation</h1> <h1 class="title">Ising model simulation</h1>
<p class="byline">February 4, 2018</p> <p class="byline">February 4, 2018</p>
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<h1 class="title">L-systems</h1> <h1 class="title">L-systems</h1>
<p class="byline">January 17, 2018</p> <p class="byline">January 17, 2018</p>
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<h1 class="title">Orbit</h1> <h1 class="title">Orbit</h1>
<p class="byline">July 26, 2017</p> <p class="byline">July 26, 2017</p>
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<h1 class="title">Satrap</h1> <h1 class="title">Satrap</h1>
<p class="byline">July 26, 2017</p> <p class="byline">July 26, 2017</p>
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<h1 class="title">Topological Data Analysis of time-dependent networks</h1> <h1 class="title">Topological Data Analysis of time-dependent networks</h1>
<p class="byline">September 1, 2018</p> <p class="byline">September 1, 2018</p>
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<h1 class="title">WWII bombings visualization</h1> <h1 class="title">WWII bombings visualization</h1>
<p class="byline">July 26, 2017</p> <p class="byline">July 26, 2017</p>
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<title>Dyalog APL Problem Solving Competition 2020 — Phase II</title> <title>Dyalog APL Problem Solving Competition 2020 — Phase II</title>
<link>https://www.lozeve.com/posts/dyalog-apl-competition-2020-phase-2.html</link> <link>https://www.lozeve.com/posts/dyalog-apl-competition-2020-phase-2.html</link>
<description><![CDATA[<article> <description><![CDATA[<section>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction">Introduction</a></li> <li><a href="#introduction">Introduction</a></li>
<li><a href="#problem-1-take-a-dive">Problem 1 – Take a Dive</a></li> <li><a href="#problem-1-take-a-dive">Problem 1 – Take a Dive</a></li>
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<div class="sourceCode" id="cb21"><pre class="sourceCode default"><code class="sourceCode default"><span id="cb21-1"><a href="#cb21-1" aria-hidden="true"></a> :EndNamespace</span> <div class="sourceCode" id="cb21"><pre class="sourceCode default"><code class="sourceCode default"><span id="cb21-1"><a href="#cb21-1" aria-hidden="true"></a> :EndNamespace</span>
<span id="cb21-2"><a href="#cb21-2" aria-hidden="true"></a>:EndNamespace</span></code></pre></div> <span id="cb21-2"><a href="#cb21-2" aria-hidden="true"></a>:EndNamespace</span></code></pre></div>
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]]></description> ]]></description>
<pubDate>Sun, 02 Aug 2020 00:00:00 UT</pubDate> <pubDate>Sun, 02 Aug 2020 00:00:00 UT</pubDate>
<guid>https://www.lozeve.com/posts/dyalog-apl-competition-2020-phase-2.html</guid> <guid>https://www.lozeve.com/posts/dyalog-apl-competition-2020-phase-2.html</guid>
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<title>Dyalog APL Problem Solving Competition 2020 — Phase I</title> <title>Dyalog APL Problem Solving Competition 2020 — Phase I</title>
<link>https://www.lozeve.com/posts/dyalog-apl-competition-2020-phase-1.html</link> <link>https://www.lozeve.com/posts/dyalog-apl-competition-2020-phase-1.html</link>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction">Introduction</a></li> <li><a href="#introduction">Introduction</a></li>
<li><a href="#lets-split">1. Let’s Split!</a></li> <li><a href="#lets-split">1. Let’s Split!</a></li>
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<span id="cb6-12"><a href="#cb6-12" aria-hidden="true"></a> ─────────────────────────────────────────────────────────────┘</span></code></pre></div> <span id="cb6-12"><a href="#cb6-12" aria-hidden="true"></a> ─────────────────────────────────────────────────────────────┘</span></code></pre></div>
<p>Next, we clean this up with Ravel (<code>,</code>) and we can Mix to obtain the final result.</p> <p>Next, we clean this up with Ravel (<code>,</code>) and we can Mix to obtain the final result.</p>
</section> </section>
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<pubDate>Sun, 02 Aug 2020 00:00:00 UT</pubDate> <pubDate>Sun, 02 Aug 2020 00:00:00 UT</pubDate>
<guid>https://www.lozeve.com/posts/dyalog-apl-competition-2020-phase-1.html</guid> <guid>https://www.lozeve.com/posts/dyalog-apl-competition-2020-phase-1.html</guid>
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<title>Operations Research and Optimization: where to start?</title> <title>Operations Research and Optimization: where to start?</title>
<link>https://www.lozeve.com/posts/operations-research-references.html</link> <link>https://www.lozeve.com/posts/operations-research-references.html</link>
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<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction">Introduction</a></li> <li><a href="#introduction">Introduction</a></li>
<li><a href="#why-is-it-hard-to-approach">Why is it hard to approach?</a></li> <li><a href="#why-is-it-hard-to-approach">Why is it hard to approach?</a></li>
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<pubDate>Wed, 27 May 2020 00:00:00 UT</pubDate> <pubDate>Wed, 27 May 2020 00:00:00 UT</pubDate>
<guid>https://www.lozeve.com/posts/operations-research-references.html</guid> <guid>https://www.lozeve.com/posts/operations-research-references.html</guid>
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<item> <item>
<title>ICLR 2020 Notes: Speakers and Workshops</title> <title>ICLR 2020 Notes: Speakers and Workshops</title>
<link>https://www.lozeve.com/posts/iclr-2020-notes.html</link> <link>https://www.lozeve.com/posts/iclr-2020-notes.html</link>
<description><![CDATA[<article> <description><![CDATA[<section>
<section class="header">
</section>
<section>
<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#the-format-of-the-virtual-conference">The Format of the Virtual Conference</a></li> <li><a href="#the-format-of-the-virtual-conference">The Format of the Virtual Conference</a></li>
<li><a href="#speakers">Speakers</a> <li><a href="#speakers">Speakers</a>
@ -593,7 +574,6 @@
<h3 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></h3> <h3 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></h3>
<p>I didn’t attend this workshop, but I think I will watch the presentations if I can find the 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> <p>I didn’t attend this workshop, but I think I will watch the presentations if I can find the 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> </section>
</article>
]]></description> ]]></description>
<pubDate>Tue, 05 May 2020 00:00:00 UT</pubDate> <pubDate>Tue, 05 May 2020 00:00:00 UT</pubDate>
<guid>https://www.lozeve.com/posts/iclr-2020-notes.html</guid> <guid>https://www.lozeve.com/posts/iclr-2020-notes.html</guid>
@ -602,11 +582,7 @@
<item> <item>
<title>Reading notes: Hierarchical Optimal Transport for Document Representation</title> <title>Reading notes: Hierarchical Optimal Transport for Document Representation</title>
<link>https://www.lozeve.com/posts/hierarchical-optimal-transport-for-document-classification.html</link> <link>https://www.lozeve.com/posts/hierarchical-optimal-transport-for-document-classification.html</link>
<description><![CDATA[<article> <description><![CDATA[<section>
<section class="header">
</section>
<section>
<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction-and-motivation">Introduction and motivation</a></li> <li><a href="#introduction-and-motivation">Introduction and motivation</a></li>
<li><a href="#background-optimal-transport">Background: optimal transport</a></li> <li><a href="#background-optimal-transport">Background: optimal transport</a></li>
@ -694,7 +670,6 @@ W_1(p, q) = \min_{P \in \mathbb{R}_+^{n\times m}} \sum_{i,j} C_{i,j} P_{i,j}
</div> </div>
</div> </div>
</section> </section>
</article>
]]></description> ]]></description>
<pubDate>Sun, 05 Apr 2020 00:00:00 UT</pubDate> <pubDate>Sun, 05 Apr 2020 00:00:00 UT</pubDate>
<guid>https://www.lozeve.com/posts/hierarchical-optimal-transport-for-document-classification.html</guid> <guid>https://www.lozeve.com/posts/hierarchical-optimal-transport-for-document-classification.html</guid>
@ -703,11 +678,7 @@ W_1(p, q) = \min_{P \in \mathbb{R}_+^{n\times m}} \sum_{i,j} C_{i,j} P_{i,j}
<item> <item>
<title>Mindsay: Towards Self-Learning Chatbots</title> <title>Mindsay: Towards Self-Learning Chatbots</title>
<link>https://www.lozeve.com/posts/self-learning-chatbots-destygo.html</link> <link>https://www.lozeve.com/posts/self-learning-chatbots-destygo.html</link>
<description><![CDATA[<article> <description><![CDATA[<section>
<section class="header">
</section>
<section>
<p>Last week I made a presentation at the <a href="https://www.meetup.com/Paris-NLP/">Paris NLP Meetup</a>, on how we implemented self-learning chatbots in production at Mindsay.</p> <p>Last week I made a presentation at the <a href="https://www.meetup.com/Paris-NLP/">Paris NLP Meetup</a>, on how we implemented self-learning chatbots in production at Mindsay.</p>
<p>It was fascinating to other people interested in NLP about the technologies and models we deploy at work! It’s always nice to have some feedback about our work, and preparing this talk forced me to take a step back about what we do and rethink it in new interesting ways.</p> <p>It was fascinating to other people interested in NLP about the technologies and models we deploy at work! It’s always nice to have some feedback about our work, and preparing this talk forced me to take a step back about what we do and rethink it in new interesting ways.</p>
<p>Also check out the <a href="https://nlpparis.wordpress.com/2019/03/29/paris-nlp-season-3-meetup-4-at-meilleursagents/">other presentations</a>, one about diachronic (i.e. time-dependent) word embeddings and the other about the different models and the use of Knowledge Bases for Information Retrieval. (This might even give us new ideas to explore…)</p> <p>Also check out the <a href="https://nlpparis.wordpress.com/2019/03/29/paris-nlp-season-3-meetup-4-at-meilleursagents/">other presentations</a>, one about diachronic (i.e. time-dependent) word embeddings and the other about the different models and the use of Knowledge Bases for Information Retrieval. (This might even give us new ideas to explore…)</p>
@ -715,7 +686,6 @@ W_1(p, q) = \min_{P \in \mathbb{R}_+^{n\times m}} \sum_{i,j} C_{i,j} P_{i,j}
<p><strong><strong>Update:</strong></strong> The videos are now available on the <a href="https://nlpparis.wordpress.com/2019/03/29/paris-nlp-season-3-meetup-4-at-meilleursagents/">NLP Meetup website</a>.</p> <p><strong><strong>Update:</strong></strong> The videos are now available on the <a href="https://nlpparis.wordpress.com/2019/03/29/paris-nlp-season-3-meetup-4-at-meilleursagents/">NLP Meetup website</a>.</p>
<p><strong><strong>Update 2:</strong></strong> Destygo changed its name to <a href="https://www.mindsay.com/">Mindsay</a>!</p> <p><strong><strong>Update 2:</strong></strong> Destygo changed its name to <a href="https://www.mindsay.com/">Mindsay</a>!</p>
</section> </section>
</article>
]]></description> ]]></description>
<pubDate>Sat, 06 Apr 2019 00:00:00 UT</pubDate> <pubDate>Sat, 06 Apr 2019 00:00:00 UT</pubDate>
<guid>https://www.lozeve.com/posts/self-learning-chatbots-destygo.html</guid> <guid>https://www.lozeve.com/posts/self-learning-chatbots-destygo.html</guid>
@ -724,11 +694,7 @@ W_1(p, q) = \min_{P \in \mathbb{R}_+^{n\times m}} \sum_{i,j} C_{i,j} P_{i,j}
<item> <item>
<title>Random matrices from the Ginibre ensemble</title> <title>Random matrices from the Ginibre ensemble</title>
<link>https://www.lozeve.com/posts/ginibre-ensemble.html</link> <link>https://www.lozeve.com/posts/ginibre-ensemble.html</link>
<description><![CDATA[<article> <description><![CDATA[<section>
<section class="header">
</section>
<section>
<h3 id="ginibre-ensemble-and-its-properties">Ginibre ensemble and its properties</h3> <h3 id="ginibre-ensemble-and-its-properties">Ginibre ensemble and its properties</h3>
<p>The <em>Ginibre ensemble</em> is a set of random matrices with the entries chosen independently. Each entry of a <span class="math inline">\(n \times n\)</span> matrix is a complex number, with both the real and imaginary part sampled from a normal distribution of mean zero and variance <span class="math inline">\(1/2n\)</span>.</p> <p>The <em>Ginibre ensemble</em> is a set of random matrices with the entries chosen independently. Each entry of a <span class="math inline">\(n \times n\)</span> matrix is a complex number, with both the real and imaginary part sampled from a normal distribution of mean zero and variance <span class="math inline">\(1/2n\)</span>.</p>
<p>Random matrices distributions are very complex and are a very active subject of research. I stumbled on this example while reading an article in <em>Notices of the AMS</em> by Brian C. Hall <a href="#ref-1">(1)</a>.</p> <p>Random matrices distributions are very complex and are a very active subject of research. I stumbled on this example while reading an article in <em>Notices of the AMS</em> by Brian C. Hall <a href="#ref-1">(1)</a>.</p>
@ -755,7 +721,6 @@ W_1(p, q) = \min_{P \in \mathbb{R}_+^{n\times m}} \sum_{i,j} C_{i,j} P_{i,j}
<li><span id="ref-2"></span>Ginibre, Jean. “Statistical ensembles of complex, quaternion, and real matrices.” Journal of Mathematical Physics 6.3 (1965): 440-449. <a href="https://doi.org/10.1063/1.1704292">https://doi.org/10.1063/1.1704292</a></li> <li><span id="ref-2"></span>Ginibre, Jean. “Statistical ensembles of complex, quaternion, and real matrices.” Journal of Mathematical Physics 6.3 (1965): 440-449. <a href="https://doi.org/10.1063/1.1704292">https://doi.org/10.1063/1.1704292</a></li>
</ol> </ol>
</section> </section>
</article>
]]></description> ]]></description>
<pubDate>Wed, 20 Mar 2019 00:00:00 UT</pubDate> <pubDate>Wed, 20 Mar 2019 00:00:00 UT</pubDate>
<guid>https://www.lozeve.com/posts/ginibre-ensemble.html</guid> <guid>https://www.lozeve.com/posts/ginibre-ensemble.html</guid>
@ -764,11 +729,7 @@ W_1(p, q) = \min_{P \in \mathbb{R}_+^{n\times m}} \sum_{i,j} C_{i,j} P_{i,j}
<item> <item>
<title>Peano Axioms</title> <title>Peano Axioms</title>
<link>https://www.lozeve.com/posts/peano.html</link> <link>https://www.lozeve.com/posts/peano.html</link>
<description><![CDATA[<article> <description><![CDATA[<section>
<section class="header">
</section>
<section>
<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#introduction">Introduction</a></li> <li><a href="#introduction">Introduction</a></li>
<li><a href="#the-axioms">The Axioms</a></li> <li><a href="#the-axioms">The Axioms</a></li>
@ -891,7 +852,6 @@ then <span class="math inline">\(\varphi(n)\)</span> is true for every natural n
</div> </div>
</div> </div>
</section> </section>
</article>
]]></description> ]]></description>
<pubDate>Mon, 18 Mar 2019 00:00:00 UT</pubDate> <pubDate>Mon, 18 Mar 2019 00:00:00 UT</pubDate>
<guid>https://www.lozeve.com/posts/peano.html</guid> <guid>https://www.lozeve.com/posts/peano.html</guid>
@ -900,11 +860,7 @@ then <span class="math inline">\(\varphi(n)\)</span> is true for every natural n
<item> <item>
<title>Quick Notes on Reinforcement Learning</title> <title>Quick Notes on Reinforcement Learning</title>
<link>https://www.lozeve.com/posts/reinforcement-learning-1.html</link> <link>https://www.lozeve.com/posts/reinforcement-learning-1.html</link>
<description><![CDATA[<article> <description><![CDATA[<section>
<section class="header">
</section>
<section>
<h2 id="introduction">Introduction</h2> <h2 id="introduction">Introduction</h2>
<p>In this series of blog posts, I intend to write my notes as I go through Richard S. Sutton’s excellent <em>Reinforcement Learning: An Introduction</em> <a href="#ref-1">(1)</a>.</p> <p>In this series of blog posts, I intend to write my notes as I go through Richard S. Sutton’s excellent <em>Reinforcement Learning: An Introduction</em> <a href="#ref-1">(1)</a>.</p>
<p>I will try to formalise the maths behind it a little bit, mainly because I would like to use it as a useful personal reference to the main concepts in RL. I will probably add a few remarks about a possible implementation as I go on.</p> <p>I will try to formalise the maths behind it a little bit, mainly because I would like to use it as a useful personal reference to the main concepts in RL. I will probably add a few remarks about a possible implementation as I go on.</p>
@ -994,7 +950,6 @@ q_{\pi}(s,a) &amp;= \mathbb{E}_{\pi}\left[ \sum_{k=0}^{\infty} \gamma^k R_{t+k+1
<li><span id="ref-1"></span>R. S. Sutton and A. G. Barto, Reinforcement learning: an introduction, Second edition. Cambridge, MA: The MIT Press, 2018.</li> <li><span id="ref-1"></span>R. S. Sutton and A. G. Barto, Reinforcement learning: an introduction, Second edition. Cambridge, MA: The MIT Press, 2018.</li>
</ol> </ol>
</section> </section>
</article>
]]></description> ]]></description>
<pubDate>Wed, 21 Nov 2018 00:00:00 UT</pubDate> <pubDate>Wed, 21 Nov 2018 00:00:00 UT</pubDate>
<guid>https://www.lozeve.com/posts/reinforcement-learning-1.html</guid> <guid>https://www.lozeve.com/posts/reinforcement-learning-1.html</guid>
@ -1003,11 +958,7 @@ q_{\pi}(s,a) &amp;= \mathbb{E}_{\pi}\left[ \sum_{k=0}^{\infty} \gamma^k R_{t+k+1
<item> <item>
<title>Ising model simulation in APL</title> <title>Ising model simulation in APL</title>
<link>https://www.lozeve.com/posts/ising-apl.html</link> <link>https://www.lozeve.com/posts/ising-apl.html</link>
<description><![CDATA[<article> <description><![CDATA[<section>
<section class="header">
</section>
<section>
<div id="toc"><h2>Table of Contents</h2><ul> <div id="toc"><h2>Table of Contents</h2><ul>
<li><a href="#the-apl-family-of-languages">The APL family of languages</a> <li><a href="#the-apl-family-of-languages">The APL family of languages</a>
<ul> <ul>
@ -1207,7 +1158,6 @@ q_{\pi}(s,a) &amp;= \mathbb{E}_{\pi}\left[ \sum_{k=0}^{\infty} \gamma^k R_{t+k+1
<p>It took me some time to write this, but Dyalog’s tools make it really easy to insert symbols and to look up what they do. Next time, I will look into some ASCII-based APL descendants. J seems to have a <a href="http://code.jsoftware.com/wiki/NuVoc">good documentation</a> and a tradition of <em>tacit definitions</em>, similar to the point-free style in Haskell. Overall, J seems well-suited to modern functional programming, while APL is still under the influence of its early days when it was more procedural. Another interesting area is K, Q, and their database engine kdb+, which seems to be extremely performant and actually used in production.</p> <p>It took me some time to write this, but Dyalog’s tools make it really easy to insert symbols and to look up what they do. Next time, I will look into some ASCII-based APL descendants. J seems to have a <a href="http://code.jsoftware.com/wiki/NuVoc">good documentation</a> and a tradition of <em>tacit definitions</em>, similar to the point-free style in Haskell. Overall, J seems well-suited to modern functional programming, while APL is still under the influence of its early days when it was more procedural. Another interesting area is K, Q, and their database engine kdb+, which seems to be extremely performant and actually used in production.</p>
<p>Still, Unicode symbols make the code much more readable, mainly because there is a one-to-one link between symbols and functions, which cannot be maintained with only a few ASCII characters.</p> <p>Still, Unicode symbols make the code much more readable, mainly because there is a one-to-one link between symbols and functions, which cannot be maintained with only a few ASCII characters.</p>
</section> </section>
</article>
]]></description> ]]></description>
<pubDate>Mon, 05 Mar 2018 00:00:00 UT</pubDate> <pubDate>Mon, 05 Mar 2018 00:00:00 UT</pubDate>
<guid>https://www.lozeve.com/posts/ising-apl.html</guid> <guid>https://www.lozeve.com/posts/ising-apl.html</guid>

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</head> </head>
<body> <body>
<article> <article>
<header> <header>
<nav> <nav>
<a href="./">Home</a> <a href="./">Home</a>
<a href="./archive.html">Posts</a>
<a href="./projects.html">Projects</a> <a href="./projects.html">Projects</a>
<a href="./archive.html">Archive</a>
<a href="./contact.html">Contact</a> <a href="./contact.html">Contact</a>
</nav> </nav>
<h1 class="title">Skills in Statistics, Data Science and Machine Learning</h1> <h1 class="title">Skills in Statistics, Data Science and Machine Learning</h1>
</header> </header>
</article>
<h2 id="statistics">Statistics</h2> <h2 id="statistics">Statistics</h2>
<ul> <ul>
<li>Knowledge of Linear Models and Generalised Linear Models (including logistic regression), both in theory and in applications</li> <li>Knowledge of Linear Models and Generalised Linear Models (including logistic regression), both in theory and in applications</li>
@ -95,6 +93,8 @@
<li>Hidden Markov Models and Sequential Monte Carlo Methods</li> <li>Hidden Markov Models and Sequential Monte Carlo Methods</li>
</ul> </ul>
</article>
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display: inline-block; display: inline-block;
font-size: 1.4rem; font-size: 1.4rem;
font-weight: bold; font-weight: bold;
text-decoration: none !important; font-variant-caps: small-caps;
margin: 0 0.5rem; margin: 0 0.5rem;
padding: 0 0; padding: 0 0;
} }
@ -40,16 +40,12 @@ article .header {
/* } */ /* } */
blockquote { blockquote {
display: block;
border-left: 2px solid #808080; border-left: 2px solid #808080;
padding-left: 1rem; padding-left: 1rem;
margin-top: 1rem;
margin-bottom: 1rem;
color: #333;
background: #eeeeee;
} }
.definition, .proposition, .theorem { .definition, .proposition, .theorem {
width: 55%;
display: block; display: block;
border-left: 2px solid #808080; border-left: 2px solid #808080;
padding-left: 1rem; padding-left: 1rem;
@ -89,6 +85,10 @@ blockquote {
font-style: normal; font-style: normal;
} }
.proof {
width: 55%;
}
.proof:before { .proof:before {
content: "Proof."; content: "Proof.";
font-style: italic; font-style: italic;

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title: Home title: Dimitri Lozeve
--- ---
<img src="/images/portrait_small.jpg" style="width: 25%; float: right; margin-left: 10px; margin-bottom: 10px; margin-right: 50px; margin-top: -100px" alt="Dimitri Lozeve portrait"/> <img src="/images/portrait_small.jpg" style="width: 25%; float: right; margin-left: 10px; margin-bottom: 10px; margin-right: 50px; margin-top: -100px" alt="Dimitri Lozeve portrait"/>

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</head> </head>
<body> <body>
<article> <article>
$if(title)$
<header> <header>
<nav> <nav>
<a href="/">Home</a> <a href="/">Home</a>
<a href="/archive.html">Posts</a>
<a href="/projects.html">Projects</a> <a href="/projects.html">Projects</a>
<a href="/archive.html">Archive</a>
<a href="/contact.html">Contact</a> <a href="/contact.html">Contact</a>
</nav> </nav>
$if(title)$
<h1 class="title">$title$</h1> <h1 class="title">$title$</h1>
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<p class="subtitle">$subtitle$</p> <p class="subtitle">$subtitle$</p>
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$endif$ $endif$
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