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Poster
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Wed 18:30
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Sample-Optimal Parametric Q-Learning Using Linearly Additive Features
Lin Yang · Mengdi Wang
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Poster
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Tue 18:30
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Doubly-Competitive Distribution Estimation
Yi Hao · Alon Orlitsky
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Poster
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Tue 18:30
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Generalized No Free Lunch Theorem for Adversarial Robustness
Elvis Dohmatob
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Poster
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Tue 18:30
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CapsAndRuns: An Improved Method for Approximately Optimal Algorithm Configuration
Gellért Weisz · András György · Csaba Szepesvari
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Poster
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Wed 18:30
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The Odds are Odd: A Statistical Test for Detecting Adversarial Examples
Kevin Roth · Yannic Kilcher · Thomas Hofmann
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Poster
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Tue 18:30
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Information-Theoretic Considerations in Batch Reinforcement Learning
Jinglin Chen · Nan Jiang
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Poster
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Thu 18:30
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Communication-Constrained Inference and the Role of Shared Randomness
Jayadev Acharya · Clément Canonne · Himanshu Tyagi
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Poster
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Wed 18:30
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Towards Understanding Knowledge Distillation
Mary Phuong · Christoph H. Lampert
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Poster
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Tue 18:30
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Bayesian Counterfactual Risk Minimization
Ben London · Ted Sandler
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Poster
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Tue 18:30
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Rademacher Complexity for Adversarially Robust Generalization
Dong Yin · Kannan Ramchandran · Peter Bartlett
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Poster
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Thu 18:30
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Discovering Conditionally Salient Features with Statistical Guarantees
Jaime Roquero Gimenez · James Zou
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Poster
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Thu 18:30
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Online Adaptive Principal Component Analysis and Its extensions
Jianjun Yuan · Andrew Lamperski
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