Does Momentum Help? A Sample Complexity Analysis. - Gugan Thoppe; Rohan Deb; Swetha Ganesh; Amarjit Budhiraja (CoRR, 2021)

Online Learning with Adversaries: A Differential-Inclusion Analysis. - Swetha Ganesh; Alexandre Reiffers-Masson; Gugan Thoppe (CDC, 2023)

Does Momentum Help in Stochastic Optimization? A Sample Complexity Analysis. - Swetha Ganesh; Rohan Deb; Gugan Thoppe; Amarjit Budhiraja (UAI, 2023)

Variance-Reduced Policy Gradient Approaches for Infinite Horizon Average Reward Markov Decision Processes. - Swetha Ganesh; Washim Uddin Mondal; Vaneet Aggarwal (CoRR, 2024)

An Accelerated Multi-level Monte Carlo Approach for Average Reward Reinforcement Learning with General Policy Parametrization. - Swetha Ganesh; Vaneet Aggarwal (CoRR, 2024)

Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries. - Swetha Ganesh; Jiayu Chen; Gugan Thoppe; Vaneet Aggarwal (Trans. Mach. Learn. Res., 2024)

Order-Optimal Regret with Novel Policy Gradient Approaches in Infinite-Horizon Average Reward MDPs. - Swetha Ganesh; Washim Uddin Mondal; Vaneet Aggarwal (AISTATS, 2025)

Order-Optimal Global Convergence for Actor-Critic with General Policy and Neural Critic Parametrization. - Swetha Ganesh; Jiayu Chen; Washim Uddin Mondal; Vaneet Aggarwal (UAI, 2025)

Global Convergence for Average Reward Constrained MDPs with Primal-Dual Actor Critic Algorithm. - Yang Xu 003; Swetha Ganesh; Washim Uddin Mondal; Qinbo Bai; Vaneet Aggarwal (CoRR, 2025)

Regret Analysis of Average-Reward Unichain MDPs via an Actor-Critic Approach. - Swetha Ganesh; Vaneet Aggarwal (CoRR, 2025)

Efficient Q-Learning and Actor-Critic Methods for Robust Average Reward Reinforcement Learning. - Yang Xu 003; Swetha Ganesh; Vaneet Aggarwal (CoRR, 2025)