Shao, Han

15 publications

NeurIPS 2025 How Many Domains Suffice for Domain Generalization? a Tight Characterization via the Domain Shattering Dimension Cynthia Dwork, Lunjia Hu, Han Shao

NeurIPS 2025 Probably Approximately Precision and Recall Learning Lee Cohen, Yishay Mansour, Shay Moran, Han Shao

ICML 2025 Should Decision-Makers Reveal Classifiers in Online Strategic Classification? Han Shao, Shuo Xie, Kunhe Yang

COLT 2024 Learnability Gaps of Strategic Classification Lee Cohen, Yishay Mansour, Shay Moran, Han Shao

NeurIPS 2024 Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization Omar Montasser, Han Shao, Emmanuel Abbe

NeurIPS 2023 Eliciting User Preferences for Personalized Multi-Objective Decision Making Through Comparative Feedback Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew Walter

NeurIPS 2023 Strategic Classification Under Unknown Personalized Manipulation Han Shao, Avrim Blum, Omar Montasser

NeurIPS 2022 A Theory of PAC Learnability Under Transformation Invariances Han Shao, Omar Montasser, Avrim Blum

NeurIPS 2021 Accurately Solving Rod Dynamics with Graph Learning Han Shao, Tassilo Kugelstadt, Torsten Hädrich, Wojtek Palubicki, Jan Bender, Soeren Pirk, Dominik L Michels

ICML 2021 One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao

COLT 2021 Robust Learning Under Clean-Label Attack Avrim Blum, Steve Hanneke, Jian Qian, Han Shao

NeurIPS 2020 Online Learning with Primary and Secondary Losses Avrim Blum, Han Shao

ICML 2020 Structure Adaptive Algorithms for Stochastic Bandits Rémy Degenne, Han Shao, Wouter Koolen

NeurIPS 2018 Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs Han Shao, Xiaotian Yu, Irwin King, Michael R Lyu

UAI 2018 Pure Exploration of Multi-Armed Bandits with Heavy-Tailed Payoffs Xiaotian Yu, Han Shao, Michael R. Lyu, Irwin King