• Click on the titles of individual talks for abstract, slides and archived video.

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TUTORIAL: Algorithmic Approaches to Preventing Overfitting in Adaptive Data Analysis I
Aaron Roth (University of Pennsylvania)
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Break
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TUTORIAL: Algorithmic Approaches to Preventing Overfitting in Adaptive Data Analysis II
Adam Smith (Boston University)
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Controlling FDR While Sorting Through Discoveries
Chiara Sabatti (Stanford University)
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Lunch
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Generalization for Adaptively-chosen Estimators via Stable Median
Thomas Steinke (IBM Almaden)
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The Everlasting Database: Statistical Validity at a Fair Price
Blake Woodworth (Toyota Technological Institute at Chicago)
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Break
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Information-theoretic Analysis of Algorithmic Stability
Max Raginsky (UIUC)
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Moritz Hardt
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Break
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Impromptu Short Talks & Discussions (James, Pragya, Robin)
James Zou (Stanford University)
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Group Dinner (Henry's at The Graduate Hotel)
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TUTORIAL: Recent Developments in Selective Inference I
Snigdha Panigrahi (Stanford University)
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Break
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TUTORIAL: Recent Developments in Selective Inference II
Snigdha Panigrahi (Stanford University)
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Minimax Rates for Batched Stochastic Optimization
John Duchi (Stanford University)
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Lunch
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AdaPT: An Interactive Procedure for Multiple Testing with Side Information
Will Fithian (UC Berkeley)
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Private False Discovery Rate Control, with Insights into Good Dependence Structures of p-values
Weijie Su (University of Pennsylvania)
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Break
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How to Use Heuristics for Differential Privacy
Aaron Roth (University of Pennsylvania)
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Bayesian Models and Information Symmetry in Adaptive Data Analysis
Adam Smith (Boston University)
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Calibrating Noise to Variance in Adaptive Data Analysis
Vitaly Feldman (Google Brain)
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Break
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Impromptu Short Talks & Discussions (Om, Michael, Ludwig)
James Zou (Stanford University)
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Group Dinner (Great China Restaurant)