Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning

23 August 2020

Papers citing "Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning"

24 / 24 papers shown

Title
Robust Decentralized Learning with Local Updates and Gradient Tracking Sajjad Ghiasvand Amirhossein Reisizadeh Mahnoosh Alizadeh Ramtin Pedarsani 160 4 0 02 May 2024
Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization Wei Shen Minhui Huang Jiawei Zhang Cong Shen FedML 168 3 0 02 Nov 2023
Faster Stochastic Variance Reduction Methods for Compositional MiniMax Optimization Jin Liu Xiaokang Pan Junwen Duan Hongdong Li Youqi Li Zhe Qu 105 2 0 18 Aug 2023
Optimal Algorithms for Stochastic Bilevel Optimization under Relaxed Smoothness Conditions Xuxing Chen Tesi Xiao Krishnakumar Balasubramanian 144 27 0 21 Jun 2023
Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities Donghao Ying Yunkai Zhang Yuhao Ding Alec Koppel Javad Lavaei 128 15 0 27 May 2023
Federated Compositional Deep AUC Maximization Xinwen Zhang Yihang Zhang Tianbao Yang Richard Souvenir Hongchang Gao FedML 168 9 0 20 Apr 2023
PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities Zhuqing Liu Xin Zhang Songtao Lu Jia-Wei Liu 90 8 0 05 Mar 2023
Federated Minimax Optimization with Client Heterogeneity Pranay Sharma Rohan Panda Gauri Joshi FedML 136 10 0 08 Feb 2023
A first-order augmented Lagrangian method for constrained minimax optimization Zhaosong Lu Sanyou Mei 198 6 0 05 Jan 2023
Iterative Minimax Games with Coupled Linear Constraints Hui-Li Zhang Junlin Wang Zi Xu 305 4 0 09 Dec 2022
Decentralized Stochastic Gradient Descent Ascent for Finite-Sum Minimax Problems Hongchang Gao 144 17 0 06 Dec 2022
An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization Le‐Yu Chen Haishan Ye Luo Luo 245 10 0 05 Dec 2022
Tight Analysis of Extra-gradient and Optimistic Gradient Methods For Nonconvex Minimax Problems Pouria Mahdavinia Yuyang Deng Haochuan Li M. Mahdavi 148 13 0 17 Oct 2022
A Single-Timescale Analysis For Stochastic Approximation With Multiple Coupled Sequences Han Shen Tianyi Chen 140 19 0 21 Jun 2022
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms Pranay Sharma Rohan Panda Gauri Joshi P. Varshney FedML 156 52 0 09 Mar 2022
Differentially Private Temporal Difference Learning with Stochastic Nonconvex-Strongly-Concave Optimization Canzhe Zhao Yanjie Ze Jing Dong Baoxiang Wang Shuai Li 117 5 0 25 Jan 2022
Accelerated Proximal Alternating Gradient-Descent-Ascent for Nonconvex Minimax Machine Learning Ziyi Chen Shaocong Ma Yi Zhou 185 8 0 22 Dec 2021
Randomized Stochastic Gradient Descent Ascent Othmane Sebbouh Marco Cuturi Gabriel Peyré 530 7 0 25 Nov 2021
A Cubic Regularization Approach for Finding Local Minimax Points in Nonconvex Minimax Optimization Ziyi Chen Zhengyang Hu Qunwei Li Zhe Wang Yi Zhou 152 7 0 14 Oct 2021
Finding Second-Order Stationary Points in Nonconvex-Strongly-Concave Minimax Optimization Luo Luo Yujun Li Cheng Chen 133 15 0 10 Oct 2021
CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems Jiahao Xie Chao Zhang Zebang Shen Weijie Liu Hui Qian FedML 106 2 0 29 May 2021
Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry Ziyi Chen Yi Zhou Tengyu Xu Yingbin Liang 169 35 0 09 Feb 2021
Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms Tengyu Xu Yingbin Liang 139 26 0 10 Nov 2020
Temporal-difference learning with nonlinear function approximation: lazy training and mean field regimes Andrea Agazzi Jianfeng Lu 185 8 0 27 May 2019