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Oral
Wed Jun 12 08:00 AM -- 08:20 AM (KST) @ Room 103
Natural Analysts in Adaptive Data Analysis
In Statistical Learning Theory
Tijana Zrnic · Moritz Hardt
[ Slides]  [ Video] 
Oral
Wed Jun 12 08:20 AM -- 08:25 AM (KST) @ Room 103
CapsAndRuns: An Improved Method for Approximately Optimal Algorithm Configuration
In Statistical Learning Theory
Gellért Weisz · András György · Csaba Szepesvari
[ Slides]  [ Video] 
Oral
Wed Jun 12 08:25 AM -- 08:30 AM (KST) @ Room 103
Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction
In Statistical Learning Theory
Giulia Luise · Dimitrios Stamos · Massimiliano Pontil · Carlo Ciliberto
[ Slides]  [ Video] 
Oral
Wed Jun 12 08:30 AM -- 08:35 AM (KST) @ Room 103
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
In Statistical Learning Theory
Andrew Cotter · Maya Gupta · Heinrich Jiang · Nati Srebro · Karthik Sridharan · Serena Wang · Blake Woodworth · Seungil You
[ Slides]  [ Video] 
Oral
Wed Jun 12 08:35 AM -- 08:40 AM (KST) @ Room 103
Optimality Implies Kernel Sum Classifiers are Statistically Efficient
In Statistical Learning Theory
Raphael Meyer · Jean Honorio
[ Slides]  [ Video] 
Oral
Wed Jun 12 08:40 AM -- 09:00 AM (KST) @ Room 103
The Implicit Fairness Criterion of Unconstrained Learning
In Statistical Learning Theory
Lydia T. Liu · Max Simchowitz · Moritz Hardt
[ Video] 
Oral
Wed Jun 12 09:00 AM -- 09:05 AM (KST) @ Room 103
Weak Detection of Signal in the Spiked Wigner Model
In Statistical Learning Theory
Hye Won Chung · Ji Oon Lee
[ Slides]  [ Video] 
Oral
Wed Jun 12 09:05 AM -- 09:10 AM (KST) @ Room 103
Rademacher Complexity for Adversarially Robust Generalization
In Statistical Learning Theory
Dong Yin · Kannan Ramchandran · Peter Bartlett
[ Slides]  [ Video] 
Oral
Wed Jun 12 09:10 AM -- 09:15 AM (KST) @ Room 103
Provably efficient RL with Rich Observations via Latent State Decoding
In Statistical Learning Theory
Simon Du · Akshay Krishnamurthy · Nan Jiang · Alekh Agarwal · Miroslav Dudik · John Langford
[ Slides]  [ Video] 
Oral
Wed Jun 12 09:15 AM -- 09:20 AM (KST) @ Room 103
Information-Theoretic Considerations in Batch Reinforcement Learning
In Statistical Learning Theory
Jinglin Chen · Nan Jiang
[ Slides]  [ Video]