Han Shao

According to our database, Han Shao authored at least 25 papers between 2018 and 2026.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2026

Scale-Sensitive Shattering: Learnability and Evaluability at Optimal Scale.

Shashaank Aiyer, Yishay Mansour, Shay Moran, Han Shao, Tom Waknine

CoRR, May, 2026

Online Set Learning from Precision and Recall Feedback.

Lee Cohen, Yishay Mansour, Shay Moran, Han Shao

CoRR, May, 2026

A Theoretical Framework for Statistical Evaluability of Generative Models.

Shashaank Aiyer, Yishay Mansour, Shay Moran, Han Shao

CoRR, April, 2026

Equitable Evaluation via Elicitation.

Elbert Du, Cynthia Dwork, Lunjia Hu, Reid McIlroy-Young, Han Shao, Linjun Zhang

CoRR, February, 2026

On Randomized Algorithms in Online Strategic Classification.

Chase Hutton, Adam Melrod, Han Shao

CoRR, February, 2026

A Machine Learning Theory Perspective on Strategic Litigation.

Melissa Dutz, Han Shao, Avrim Blum, Aloni Cohen

Proceedings of the 7th Symposium on Foundations of Responsible Computing, 2026

2025

Incentives in Federated Learning with Heterogeneous Agents.

Ariel D. Procaccia, Han Shao, Itai Shapira

CoRR, September, 2025

How Many Domains Suffice for Domain Generalization? A Tight Characterization via the Domain Shattering Dimension.

Cynthia Dwork, Lunjia Hu, Han Shao

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Probably Approximately Precision and Recall Learning.

Lee Cohen, Yishay Mansour, Shay Moran, Han Shao

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Should Decision-Makers Reveal Classifiers in Online Strategic Classification?

Han Shao, Shuo Xie, Kunhe Yang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Trustworthy Machine Learning under Social and Adversarial Data Sources.

Han Shao

CoRR, 2024

Efficient Prior-Free Mechanisms for No-Regret Agents.

Natalie Collina, Aaron Roth, Han Shao

Proceedings of the 25th ACM Conference on Economics and Computation, 2024

Transformation-Invariant Learning and Theoretical Guarantees for OOD Generalization.

Omar Montasser, Han Shao, Emmanuel Abbe

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Incentivized Collaboration in Active Learning.

Lee Cohen, Han Shao

Proceedings of the 5th Symposium on Foundations of Responsible Computing, 2024

Learnability Gaps of Strategic Classification.

Lee Cohen, Yishay Mansour, Shay Moran, Han Shao

Proceedings of the Thirty Seventh Annual Conference on Learning Theory, June 30, 2024

2023

On the Effect of Defections in Federated Learning and How to Prevent Them.

Minbiao Han, Kumar Kshitij Patel, Han Shao, Lingxiao Wang

CoRR, 2023

Strategic Classification under Unknown Personalized Manipulation.

Han Shao, Avrim Blum, Omar Montasser

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback.

Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew R. Walter

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

A Theory of PAC Learnability under Transformation Invariances.

Han Shao, Omar Montasser, Avrim Blum

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

Proceedings of the 38th International Conference on Machine Learning, 2021

Robust learning under clean-label attack.

Avrim Blum, Steve Hanneke, Jian Qian, Han Shao

Proceedings of the Conference on Learning Theory, 2021

2020

Online Learning with Primary and Secondary Losses.

Avrim Blum, Han Shao

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Structure Adaptive Algorithms for Stochastic Bandits.

Rémy Degenne, Han Shao, Wouter M. Koolen

Proceedings of the 37th International Conference on Machine Learning, 2020

2018

Pure Exploration of Multi-Armed Bandits with Heavy-Tailed Payoffs.

Xiaotian Yu, Han Shao, Michael R. Lyu, Irwin King

Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, 2018

Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs.

Han Shao, Xiaotian Yu, Irwin King, Michael R. Lyu

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018