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<!DOCTYPE html>
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<title>Papers</title>
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<h1 id="indextitle">Papers</h1>
<p>Summaries of and commentary on optimization & machine learning papers.</p>
<a href="https://www.github.com/akshayka/papers"><img src="assets/github.svg"></a>
<a href="https://www.debugmind.com"><img src="assets/blog.png"></a>
<a href="https://www.akshayagrawal.com"><img src="assets/education.svg"></a>
</center>
<ol>
<li><a href="html/gubin1966projections.html">The Method of Projections for Finding the Common Point of Convex Sets <span class="year">(Gubin 1966)</span></a></li>
<li><a href="html/bomze2002sqp.html">Solving standard quadratic optimization problems via semidefinite and copositive programming <span class="year">(Bomze 2002)</span></a></li>
<li><a href="html/lofberg2004yalmip.html">YALMIP: A Toolbox for Modeling and Optimization in MATLAB <span class="year">(Lofberg 2004)</span></a></li>
<li><a href="html/grant2008graph.html">Graph Implementations for Nonsmooth Convex Programs <span class="year">(Grant 2008)</span></a></li>
<li><a href="html/chu2013socp-codegen.html">Code Generation for Embedded Second-Order Cone Programming <span class="year">(Chu 2013)</span></a></li>
<li><a href="html/gatys2015neuralstyle.html">A Neural Algorithm of Artistic Style <span class="year">(Gatys 2015)</span></a></li>
<li><a href="html/arora2016pmi-embeddings.html">A Latent Variable Model Approach to PMI-based Word Embeddings <span class="year">(Arora 2016)</span></a></li>
<li><a href="html/diamond2016cvxpy.html">CVXPY: A Python-Embedded Modeling Language for Convex Optimization <span class="year">(Diamond 2016)</span></a></li>
<li><a href="html/dunning2016jump.html">JuMP: A Modeling Language for Mathematical Optimization <span class="year">(Duninng 2016)</span></a></li>
<li><a href="html/hardt2016sgd-stability.html">Train Faster, Generalize Better: Stability of Stochastic Gradient Descent <span class="year">(Hardt 2016)</span></a></li>
<li><a href="html/monga2017tensorflow.html">TensorFlow: A System for Large-Scale Machine Learning <span class="year">(Mongat 2016)</span></a></li>
<li><a href="pdf/odonoghue2016scs.pdf">Conic Optimization via Operator Splitting and Homogeneous Self-Dual Embedding <span class="year">(O'Donoghue 2016)</span></a></li>
<li><a href="html/amos2017optnet.html">OptNet: Differentiable Optimization as a Layer in Neural Networks <span class="year">(Amos 2017)</span></a></li>
<li><a href="html/arora2017sentence-embeddings.html">A Simple but Tough-to-Beat Baseline for Sentence Embeddings <span class="year">(Arora 2017)</span></a></li>
<li><a href="html/jonas2017pywren.html">Occupy the Cloud: Distributed Computing for the 99% <span class="year">(Jonas 2017)</span></a></li>
<li><a href="html/lipton2017.html">The Mythos of Model Interpretability <span class="year">(Lipton 2017)</span></a></li>
<li><a href="html/elghaoui2018lifted.html">Lifted Neural Networks <span class="year">(El Ghaoui 2018)</span></a></li>
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