Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function

25 May 2022

Papers citing "Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function"

6 / 6 papers shown

Title
Learning Optimal Deterministic Policies with Stochastic Policy Gradients Alessandro Montenegro Marco Mussi Alberto Maria Metelli Matteo Papini 42 2 0 03 May 2024
Order-Optimal Regret with Novel Policy Gradient Approaches in Infinite-Horizon Average Reward MDPs Swetha Ganesh Washim Uddin Mondal Vaneet Aggarwal 39 3 0 02 Apr 2024
Global Convergence Guarantees for Federated Policy Gradient Methods with Adversaries Swetha Ganesh Jiayu Chen Gugan Thoppe Vaneet Aggarwal FedML 61 1 0 15 Mar 2024
Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods El Mahdi Chayti N. Doikov Martin Jaggi ODL 24 5 0 23 Feb 2023
On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method Junyu Zhang Chengzhuo Ni Zheng Yu Csaba Szepesvári Mengdi Wang 44 67 0 17 Feb 2021
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 133 1,198 0 16 Aug 2016