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<a href="posts/2019-03-14-great-but-manageable-expectations.html"><h2> Great but Manageable Expectations </h2></a>
<p>Posted on 2019-03-14</p>
<p>This is Part 2 of a two-part blog post on differential privacy. Continuing from <a href="/posts/2019-03-13-a-tail-of-two-densities.html">Part 1</a>, I discuss the Rényi differential privacy, corresponding to the Rényi divergence, a study of the moment generating functions the divergence between probability measures to derive the tail bounds.</p>
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<a href="posts/2019-03-13-a-tail-of-two-densities.html"><h2> A Tail of Two Densities </h2></a>
<p>Posted on 2019-03-13</p>
<p>This is Part 1 of a two-part post where I give an introduction to differential privacy, which is a study of tail bounds of the divergence between probability measures, with the end goal of applying it to stochastic gradient descent.</p>
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<a href="posts/2019-02-14-raise-your-elbo.html"><h2> Raise your ELBO </h2></a>
<p>Posted on 2019-02-14</p>
<p>In this post I give an introduction to variational inference, which is about maximising the evidence lower bound (ELBO).</p>
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<a href="posts/2019-01-03-discriminant-analysis.html"><h2> Discriminant analysis </h2></a>
<p>Posted on 2019-01-03</p>
<p>In this post I talk about the theory and implementation of linear and quadratic discriminant analysis, classical methods in statistical learning.</p>
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<a href="posts/2018-12-02-lime-shapley.html"><h2> Shapley, LIME and SHAP </h2></a>
<p>Posted on 2018-12-02</p>
<p>In this post I explain LIME (Ribeiro et. al. 2016), the Shapley values (Shapley, 1953) and the SHAP values (Strumbelj-Kononenko, 2014; Lundberg-Lee, 2017).</p>
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