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Poster
Tue 7:00 Concentration bounds for CVaR estimation: The cases of light-tailed and heavy-tailed distributions
Prashanth L.A. · Krishna Jagannathan · Ravi Kolla
Poster
Tue 7:00 Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks
Pranjal Awasthi · Natalie Frank · Mehryar Mohri
Poster
Tue 7:00 Tensor denoising and completion based on ordinal observations
Chanwoo Lee · Miaoyan Wang
Poster
Tue 7:00 Data Amplification: Instance-Optimal Property Estimation
Yi Hao · Alon Orlitsky
Poster
Tue 8:00 Near-optimal sample complexity bounds for learning Latent $k-$polytopes and applications to Ad-Mixtures
Chiranjib Bhattacharyya · Ravindran Kannan
Poster
Tue 8:00 Estimating the Number and Effect Sizes of Non-null Hypotheses
Jennifer Brennan · Ramya Korlakai Vinayak · Kevin Jamieson
Poster
Tue 8:00 Oracle Efficient Private Non-Convex Optimization
Seth Neel · Aaron Roth · Giuseppe Vietri · Steven Wu
Poster
Tue 9:00 Recovery of Sparse Signals from a Mixture of Linear Samples
Soumyabrata Pal · Arya Mazumdar
Poster
Tue 9:00 Learning and Sampling of Atomic Interventions from Observations
Arnab Bhattacharyya · Sutanu Gayen · Saravanan Kandasamy · Ashwin Maran · Vinodchandran N. Variyam
Poster
Tue 9:00 Tightening Exploration in Upper Confidence Reinforcement Learning
Hippolyte Bourel · Odalric-Ambrym Maillard · Mohammad Sadegh Talebi
Poster
Tue 9:00 Context Aware Local Differential Privacy
Jayadev Acharya · Kallista Bonawitz · Peter Kairouz · Daniel Ramage · Ziteng Sun
Poster
Tue 11:00 Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
Zitong Yang · Yaodong Yu · Chong You · Jacob Steinhardt · Yi Ma