141 citations · 213 across the 13 of their papers we have counts for
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Offline Reinforcement Learning via Linear-Programming with Error-Bound Induced Constraints
Asuman Ozdaglar, Sarath Pattathil, Jiawei Zhang +1
Offline reinforcement learning (RL) aims to find an optimal policy for Markov decision processes (MDPs) using a pre-collected dataset. In this work, we revisit the linear programmi…
Symmetric (Optimistic) Natural Policy Gradient for Multi-agent Learning with Parameter Convergence
Sarath Pattathil, Kaiqing Zhang, Asuman Ozdaglar
Multi-agent interactions are increasingly important in the context of reinforcement learning, and the theoretical foundations of policy gradient methods have attracted surging rese…
What is a Good Metric to Study Generalization of Minimax Learners?
Asuman Ozdaglar, Sarath Pattathil, Jiawei Zhang +1
Minimax optimization has served as the backbone of many machine learning (ML) problems. Although the convergence behavior of optimization algorithms has been extensively studied in…