Jeremy McMahan

According to our database, Jeremy McMahan authored at least 19 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Optimally Installing Strict Equilibria.

Jeremy McMahan, Young Wu, Yudong Chen, Xiaojin Zhu, Qiaomin Xie

CoRR, March, 2025

Anytime-Constrained Equilibria in Polynomial Time.

Jeremy McMahan

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

Polynomial-Time Approximability of Constrained Reinforcement Learning.

Jeremy McMahan

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

2024

Anytime-Constrained Multi-Agent Reinforcement Learning.

Jeremy McMahan, Xiaojin Zhu

CoRR, 2024

Inception: Efficiently Computable Misinformation Attacks on Markov Games.

Jeremy McMahan, Young Wu, Yudong Chen, Xiaojin Zhu, Qiaomin Xie

CoRR, 2024

Inception: Efficiently Computable Misinformation Attacks on Markov Games.

Jeremy McMahan, Young Wu, Yudong Chen, Jerry Zhu, Qiaomin Xie

RLJ, 2024

Deterministic Policies for Constrained Reinforcement Learning in Polynomial Time.

Jeremy McMahan

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

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value.

Young Wu, Jeremy McMahan, Yiding Chen, Yudong Chen, Jerry Zhu, Qiaomin Xie

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Roping in Uncertainty: Robustness and Regularization in Markov Games.

Jeremy McMahan, Giovanni Artiglio, Qiaomin Xie

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Various Misleading Visual Features in Misleading Graphs: Do they truly deceive us?

Jihyun Rho, Martina A. Rau, Shubham Kumar Bharti, Rosanne Luu, Jeremy McMahan, Andrew Wang, Jerry Zhu

Proceedings of the 46th Annual Meeting of the Cognitive Science Society, 2024

Anytime-Constrained Reinforcement Learning.

Jeremy McMahan, Xiaojin Zhu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Data Poisoning to Fake a Nash Equilibria for Markov Games.

Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Optimal Attack and Defense for Reinforcement Learning.

Jeremy McMahan, Young Wu, Xiaojin Zhu, Qiaomin Xie

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Minimally Modifying a Markov Game to Achieve Any Nash Equilibrium and Value.

Young Wu, Jeremy McMahan, Yiding Chen, Yudong Chen, Xiaojin Zhu, Qiaomin Xie

CoRR, 2023

VISER: A Tractable Solution Concept for Games with Information Asymmetry.

Jeremy McMahan, Young Wu, Yudong Chen, Xiaojin Zhu, Qiaomin Xie

CoRR, 2023

On Faking a Nash Equilibrium.

Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie

CoRR, 2023

Approximating Pandora's Box with Correlations.

Shuchi Chawla, Evangelia Gergatsouli, Jeremy McMahan, Christos Tzamos

Proceedings of the Approximation, 2023

Reward Poisoning Attacks on Offline Multi-Agent Reinforcement Learning.

Young Wu, Jeremy McMahan, Xiaojin Zhu, Qiaomin Xie

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2021

A D-competitive algorithm for the Multilevel Aggregation Problem with Deadlines.

Jeremy McMahan

CoRR, 2021