Mazumdar, Eric

21 publications

ICML 2025 Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning Laixi Shi, Jingchu Gai, Eric Mazumdar, Yuejie Chi, Adam Wierman

ICML 2025 Learning to Steer Learners in Games Yizhou Zhang, Yian Ma, Eric Mazumdar

ICLR 2025 Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning Shangding Gu, Laixi Shi, Muning Wen, Ming Jin, Eric Mazumdar, Yuejie Chi, Adam Wierman, Costas Spanos

ICLR 2025 Tractable Multi-Agent Reinforcement Learning Through Behavioral Economics Eric Mazumdar, Kishan Panaganti, Laixi Shi

NeurIPSW 2024 A Behavioral Economics Approach to Principled Multi-Agent Reinforcement Learning Eric Mazumdar, Kishan Panaganti, Laixi Shi

NeurIPS 2024 Last-Iterate Convergence for Generalized Frank-Wolfe in Monotone Variational Inequalities Zaiwei Chen, Eric Mazumdar

ICML 2024 Model-Free Robust $φ$-Divergence Reinforcement Learning Using Both Offline and Online Data Kishan Panaganti, Adam Wierman, Eric Mazumdar

NeurIPS 2024 Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms Pierre Clavier, Laixi Shi, Erwan Le Pennec, Eric Mazumdar, Adam Wierman, Matthieu Geist

ICML 2024 Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty Laixi Shi, Eric Mazumdar, Yuejie Chi, Adam Wierman

NeurIPS 2024 Understanding Model Selection for Learning in Strategic Environments Tinashe Handina, Eric Mazumdar

NeurIPS 2023 A Finite-Sample Analysis of Payoff-Based Independent Learning in Zero-Sum Stochastic Games Zaiwei Chen, Kaiqing Zhang, Eric Mazumdar, Asuman Ozdaglar, Adam Wierman

ICML 2023 Algorithmic Collective Action in Machine Learning Moritz Hardt, Eric Mazumdar, Celestine Mendler-Dünner, Tijana Zrnic

ICMLW 2023 Coupled Gradient Flows for Strategic Non-Local Distribution Shift Lauren Conger, Franca Hoffmann, Eric Mazumdar, Lillian J. Ratliff

L4DC 2023 Designing System Level Synthesis Controllers for Nonlinear Systems with Stability Guarantees Lauren E Conger, Sydney Vernon, Eric Mazumdar

NeurIPS 2023 Strategic Distribution Shift of Interacting Agents via Coupled Gradient Flows Lauren Conger, Franca Hoffmann, Eric Mazumdar, Lillian Ratliff

AISTATS 2022 Zeroth-Order Methods for Convex-Concave Min-Max Problems: Applications to Decision-Dependent Risk Minimization Chinmay Maheshwari, Chih-Yuan Chiu, Eric Mazumdar, Shankar Sastry, Lillian Ratliff

NeurIPS 2022 Decentralized, Communication- and Coordination-Free Learning in Structured Matching Markets Chinmay Maheshwari, Shankar Sastry, Eric Mazumdar

NeurIPS 2021 Global Convergence to Local Minmax Equilibrium in Classes of Nonconvex Zero-Sum Games Tanner Fiez, Lillian Ratliff, Eric Mazumdar, Evan Faulkner, Adhyyan Narang

NeurIPS 2021 Who Leads and Who Follows in Strategic Classification? Tijana Zrnic, Eric Mazumdar, Shankar Sastry, Michael I. Jordan

ICML 2020 On Approximate Thompson Sampling with Langevin Algorithms Eric Mazumdar, Aldo Pacchiano, Yian Ma, Michael Jordan, Peter Bartlett

UAI 2019 Convergence Analysis of Gradient-Based Learning in Continuous Games Benjamin Chasnov, Lillian Ratliff, Eric Mazumdar, Samuel Burden