Gradient Free Minimax Optimization: Variance Reduction and Faster Convergence

16 June 2020

Papers citing "Gradient Free Minimax Optimization: Variance Reduction and Faster Convergence"

8 / 8 papers shown

Title
Single-loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions Quanqi Hu Qi Qi Zhaosong Lu Tianbao Yang 39 2 0 28 May 2024
PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities Zhuqing Liu Xin Zhang Songtao Lu Jia-Wei Liu 40 7 0 05 Mar 2023
Decentralized Stochastic Gradient Descent Ascent for Finite-Sum Minimax Problems Hongchang Gao 24 16 0 06 Dec 2022
Zeroth-Order Alternating Gradient Descent Ascent Algorithms for a Class of Nonconvex-Nonconcave Minimax Problems Zi Xu Ziqi Wang Junlin Wang Y. Dai 18 11 0 24 Nov 2022
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization Siqi Zhang Junchi Yang Cristóbal Guzmán Negar Kiyavash Niao He 33 61 0 29 Mar 2021
Zeroth-Order Algorithms for Nonconvex Minimax Problems with Improved Complexities Zhongruo Wang Krishnakumar Balasubramanian Shiqian Ma Meisam Razaviyayn 16 25 0 22 Jan 2020
Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity S. Du Wei Hu 58 120 0 05 Feb 2018
Max-value Entropy Search for Efficient Bayesian Optimization Zi Wang Stefanie Jegelka 110 403 0 06 Mar 2017