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