Pattathil, Sarath

7 publications

COLT 2024 Autobidders with Budget and ROI Constraints: Efficiency, Regret, and Pacing Dynamics Brendan Lucier, Sarath Pattathil, Aleksandrs Slivkins, Mengxiao Zhang

ICML 2023 Revisiting the Linear-Programming Framework for Offline RL with General Function Approximation Asuman E. Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang

AISTATS 2023 Symmetric (Optimistic) Natural Policy Gradient for Multi-Agent Learning with Parameter Convergence Sarath Pattathil, Kaiqing Zhang, Asuman Ozdaglar

NeurIPS 2022 What Is a Good Metric to Study Generalization of Minimax Learners? Asuman Ozdaglar, Sarath Pattathil, Jiawei Zhang, Kaiqing Zhang

AISTATS 2020 A Unified Analysis of Extra-Gradient and Optimistic Gradient Methods for Saddle Point Problems: Proximal Point Approach Aryan Mokhtari, Asuman Ozdaglar, Sarath Pattathil

COLT 2020 Last Iterate Is Slower than Averaged Iterate in Smooth Convex-Concave Saddle Point Problems Noah Golowich, Sarath Pattathil, Constantinos Daskalakis, Asuman Ozdaglar

NeurIPS 2020 Tight Last-Iterate Convergence Rates for No-Regret Learning in Multi-Player Games Noah Golowich, Sarath Pattathil, Constantinos Daskalakis