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<ul> <li> <a href="/sponsors" title="Sponsors">Sponsors</a><br/> </li> </ul> </div> <div class="section-nav-wrapper"> <ul> <li> <a href="/stop-harassment" title="Policy Against Harassment">Policy Against Harassment</a><br/> </li> </ul> </div> <div class="section-nav-wrapper"> <ul> <li> <a href="/keynote-speakers" title="Keynote Speakers">Keynote Speakers</a><br/> </li> </ul> </div> <div class="section-nav-wrapper"> <ul> <li> <a href="https://www.acm.org/data-science-summit" title="Inaugural Event">Inaugural Event</a><br/> </li> </ul> </div> </nav> </div> <div id="main" > <div class="article" id="maincontent" tabindex="-1"> <div class="row"> <div class="acm-banner-container content-banner" style="background: url(/binaries/bannerlarge/content/gallery/acm/banners/conferences/digi-banner.jpg) no-repeat center 0 / 130% #000;"> <div class="gradient-wrapper" style="background: url('/binaries/content/gallery/global/gradient.png') repeat-x center 0 / 130% transparent;"></div> <div class="overlay" style="background: url('/binaries/content/gallery/global/tintpattern.png') repeat 0 0;"></div> <div class="row" style="margin-left: 0;"> <div class="columns large-12 medium-12 banner-content" style="padding-top: 40px !important;"> <p class="banner-heading"> <small>FODS-2020</small> ACM-IMS Foundations of Data Science Conference</p> <h2 style="margin-left: 16px;">October 19 - 20, 2020</h2></div> </div> </div> </div> <div class="row"> <div class="columns small-12"> <ul class="breadcrumbs"> <li><a href="/">Home</a></li> <li class="current"> <a href="/program">Program</a> </li> </ul> </div> </div> <article class="has-edit-button" id="SkipTarget" tabindex="-1"> <div class="row"> <div class="columns small-12"> <h1>Program</h1> </div> </div> <div class="row"> <div class="columns large-8 medium-8 small-12 blocks"> <div class="clearfix"> <p><strong><a href="https://easychair.org/smart-program/FODS2020/" target="_blank">Click here for an interactive version of the program</a>.</strong></p> <p><strong style="color:red">Program times are US Eastern Time (EDT).</strong></p> <h2 id="h-monday,-october-19th">Monday, October 19th</h2> <p><strong>09:00-12:00 EDT Session 1: Tutorial - Causal Reasoning Tutorial</strong></p> <p style="margin-left: 40px;">09:00 EDT - <strong>David Blei</strong> - <em>Causal Reasoning Tutorial</em></p> <p><strong>12:30-13:30 EDT Session 2: Keynote </strong></p> <p style="margin-left: 40px;">12:30 EDT - <strong>Mihaela van der Schaar</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416879" target="_blank"><em>AutoML and interpretability: powering the machine learning revolution in healthcare</em></a></p> <p><strong>14:00-15:30 EDT Session 3: Plenary Session - Methodology</strong></p> <p style="margin-left: 40px;">14:00 EDT - <strong>Yu Gui</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416881" target="_blank"><em>ADAGES: adaptive aggregation with stability for distributed feature selection</em></a></p> <p style="margin-left: 40px;">14:20 EDT - <strong>Chenglin Fan and Ping Li</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416886" target="_blank"><em>Classification Acceleration via Merging Decision Trees</em></a></p> <p style="margin-left: 40px;">14:40 EDT - <strong>Sarah Tan, Matvey Soloviev, Giles Hooker and Martin T. Wells</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416893" target="_blank"><em>Tree Space Prototypes: Another Look at Making Tree Ensembles Interpretable</em></a></p> <p style="margin-left: 40px;">15:00 EDT - <strong>Miguel Carreira-Perpinan and Arman Zharmagambetov</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416882" target="_blank"><em>Ensembles of bagged TAO trees consistently improve over Random Forests, AdaBoost and Gradient Boosting</em></a></p> <p><strong>15:45-17:15 EDT Session 4: Plenary Session - Fairness, Privacy, Interpretability</strong></p> <p style="margin-left: 40px;">15:45 EDT - <strong>Collin Burns, Jesse Thomason and Wesley Tansey</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416889" target="_blank"><em>Interpreting Black Box Models via Hypothesis Testing</em></a></p> <p style="margin-left: 40px;">16:05 EDT - <strong>Ruobin Gong and Xiao-Li Meng</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416892" target="_blank"><em>Congenial Differential Privacy under Mandated Disclosure</em></a></p> <p style="margin-left: 40px;">16:25 EDT - <strong>Roland Maio and Augustin Chaintreau</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416890" target="_blank"><em>Incentives Needed for Low-Cost Fair Data Reuse</em></a></p> <p style="margin-left: 40px;">16:45 EDT - <strong>Isabella Grasso, David Russell, Jeanna Matthews, Abigail Matthews and Nick Record</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416897" target="_blank"><em>Applying Algorithmic Accountability Principles and Frameworks to Ecosystem Forecasting: A Case Study in Forecasting Shellfish Toxicity in the Gulf of Maine</em></a></p> <h2 id="h-tuesday,-october-20th">Tuesday, October 20th</h2> <p><strong>09:00-12:00 EDT Session 5: Tutorial - Fairness, Privacy, and Ethics in Data Science Tutorial</strong></p> <p style="margin-left: 40px;">09:00 EDT - <strong>Michael Kearns</strong> - <em>Fairness, Privacy, and Ethics in Data Science Tutorial</em></p> <p><strong>12:30-13:30 EDT Session 6: Keynote</strong></p> <p style="margin-left: 40px;">12:30 EDT - <strong>Oren Etzioni</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416880" target="_blank"><em>Semantic Scholar, NLP, and the Fight Against COVID-19</em></a></p> <p><strong>14:00-15:50 EDT Session 7: Plenary Session - Data Science Theory</strong></p> <p style="margin-left: 40px;">14:00 EDT - <strong>Alex Fout, Bailey Fosdick and Matthew Hitt</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416887" target="_blank"><em>Non-Uniform Sampling of Fixed Margin Binary Matrices</em></a></p> <p style="margin-left: 40px;">14:20 EDT - <strong>Claire Mathieu and Michel De Rougemont</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416884" target="_blank"><em>Large very dense subgraphs in a stream of edges</em></a></p> <p style="margin-left: 40px;">14:40 EDT - <strong>Xiangyi Chen, Xiaoyun Li and Ping Li</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416891" target="_blank"><em>Toward Communication Efficient Adaptive Gradient Method</em></a></p> <p style="margin-left: 40px;">15:00 EDT - <strong>Tianyu Wang, Weicheng Ye, Dawei Geng and Cynthia Rudin</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416885" target="_blank"><em>Towards Practical Lipschitz Bandits</em></a></p> <p style="margin-left: 40px;">15:20 EDT - <strong>Devavrat Shah, Varun Somani, Qiaomin Xie and Zhi Xu</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416885" target="_blank"><em>On Reinforcement Learning for Turn-based Zero-sum Markov Games</em></a></p> <p><strong>16:00-18:00 EDT Session 8: Plenary Session - Foundations in Practice</strong></p> <p style="margin-left: 40px;">16:00 EDT - <strong>Ryan Bernstein, Matthijs Vákár and Jeannette Wing</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416896" target="_blank"><em>Transforming Probabilistic Programs for Model Checking</em></a></p> <p style="margin-left: 40px;">16:20 EDT - <strong>Haitian Chen, Bai Jiang and Hao Chen</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416895" target="_blank"><em>StyleCAPTCHA: CAPTCHA based on style-transferred images to defend against Deep Convolutional Networks</em></a></p> <p style="margin-left: 40px;">16:40 EDT - <strong>Lina Lin, Mathias Drton and Ali Shojaie</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416883" target="_blank"><em>Statistical significance in high-dimensional linear mixed models</em></a></p> <p style="margin-left: 40px;">17:00 EDT - <strong>Thanh Le and Vasant Honavar</strong> - <a href="https://dl.acm.org/doi/10.1145/3412815.3416894" target="_blank"><em>Dynamical Gaussian Process Latent Variable Model for Representation Learning from Longitudinal Data</em></a></p> <p> </p></div><!-- MainContent --> </div> <div class="columns large-4 medium-4 small-12"> </div> </div> <!-- <div class="row"> --> <!-- <div class="columns small-12"> --> <!-- 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