Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency

25 February 2021

Papers citing "Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency"

37 / 37 papers shown

Title
A stochastic smoothing framework for nonconvex-nonconcave min-sum-max problems with applications to Wasserstein distributionally robust optimization Wei Liu Muhammad Khan Gabriel Mancino-Ball Yangyang Xu 37 0 0 24 Feb 2025
GP-FL: Model-Based Hessian Estimation for Second-Order Over-the-Air Federated Learning Shayan Mohajer Hamidi Ali Bereyhi S. Asaad H. Vincent Poor 67 1 0 05 Dec 2024
Achieving Near-Optimal Convergence for Distributed Minimax Optimization with Adaptive Stepsizes Yan Huang Xiang Li Yipeng Shen Niao He Jinming Xu 33 1 0 05 Jun 2024
Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity Qihao Zhou Haishan Ye Luo Luo 24 0 0 25 May 2024
Robust Decentralized Learning with Local Updates and Gradient Tracking Sajjad Ghiasvand Amirhossein Reisizadeh Mahnoosh Alizadeh Ramtin Pedarsani 30 3 0 02 May 2024
Stochastic Smoothed Gradient Descent Ascent for Federated Minimax Optimization Wei Shen Minhui Huang Jiawei Zhang Cong Shen FedML 33 0 0 02 Nov 2023
Solving a Class of Non-Convex Minimax Optimization in Federated Learning Xidong Wu Jianhui Sun Zhengmian Hu Aidong Zhang Heng-Chiao Huang FedML 97 10 0 05 Oct 2023
Distributed Dual Coordinate Ascent with Imbalanced Data on a General Tree Network Myung Cho Lifeng Lai Weiyu Xu 14 1 0 28 Aug 2023
Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates Siqi Zhang S. Choudhury Sebastian U. Stich Nicolas Loizou FedML 19 3 0 08 Jun 2023
Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation Davoud Ataee Tarzanagh Mingchen Li Pranay Sharma Samet Oymak 24 0 0 02 Jun 2023
Near-Optimal Decentralized Momentum Method for Nonconvex-PL Minimax Problems Feihu Huang Songcan Chen 13 5 0 21 Apr 2023
Federated Compositional Deep AUC Maximization Xinwen Zhang Yihang Zhang Tianbao Yang Richard Souvenir Hongchang Gao FedML 20 7 0 20 Apr 2023
Similarity, Compression and Local Steps: Three Pillars of Efficient Communications for Distributed Variational Inequalities Aleksandr Beznosikov Martin Takáč Alexander Gasnikov 21 10 0 15 Feb 2023
Federated Minimax Optimization with Client Heterogeneity Pranay Sharma Rohan Panda Gauri Joshi FedML 30 9 0 08 Feb 2023
Global Nash Equilibrium in Non-convex Multi-player Game: Theory and Algorithms Guanpu Chen Gehui Xu Fengxiang He Yiguang Hong Leszek Rutkowski Dacheng Tao 16 5 0 19 Jan 2023
Decentralized Stochastic Gradient Descent Ascent for Finite-Sum Minimax Problems Hongchang Gao 16 16 0 06 Dec 2022
Adaptive Federated Minimax Optimization with Lower Complexities Feihu Huang Xinrui Wang Junyi Li Songcan Chen FedML 11 5 0 14 Nov 2022
Faster Adaptive Momentum-Based Federated Methods for Distributed Composition Optimization Feihu Huang FedML 20 1 0 03 Nov 2022
Fast Adaptive Federated Bilevel Optimization Feihu Huang FedML 20 7 0 02 Nov 2022
FeDXL: Provable Federated Learning for Deep X-Risk Optimization Zhishuai Guo R. L. Jin Jiebo Luo Tianbao Yang FedML 47 8 0 26 Oct 2022
$SAGDA: Achieving $\mathcal{O}(ε^{-2})$ Communication Complexity in Federated Min-Max Learning$ SAGDA: Achieving $\mathcal{O}(ε^{-2})$ Communication Complexity in Federated Min-Max Learning Haibo Yang Zhuqing Liu Xin Zhang Jia-Wei Liu FedML 28 0 0 02 Oct 2022
An Optimal Transport Approach to Personalized Federated Learning Farzan Farnia Amirhossein Reisizadeh Ramtin Pedarsani Ali Jadbabaie OT OOD FedML 29 12 0 06 Jun 2022
A Communication-efficient Algorithm with Linear Convergence for Federated Minimax Learning Zhenyu Sun Ermin Wei FedML 17 14 0 02 Jun 2022
FRAug: Tackling Federated Learning with Non-IID Features via Representation Augmentation Haokun Chen A. Frikha Denis Krompass Jindong Gu Volker Tresp OOD 30 24 0 30 May 2022
FedNest: Federated Bilevel, Minimax, and Compositional Optimization Davoud Ataee Tarzanagh Mingchen Li Christos Thrampoulidis Samet Oymak FedML 40 73 0 04 May 2022
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms Pranay Sharma Rohan Panda Gauri Joshi P. Varshney FedML 21 46 0 09 Mar 2022
Provably Efficient Convergence of Primal-Dual Actor-Critic with Nonlinear Function Approximation Jing Dong Li Shen Ying Xu Baoxiang Wang 16 1 0 28 Feb 2022
Distributed saddle point problems for strongly concave-convex functions Muhammad I. Qureshi U. Khan 31 12 0 11 Feb 2022
FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation Yan Shen Jianguo Du Hao Zhang Benyu Zhang Zhanghexuan Ji Mingchen Gao FedML 29 13 0 16 Oct 2021
Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees Aleksandr Beznosikov Peter Richtárik Michael Diskin Max Ryabinin Alexander Gasnikov FedML 15 20 0 07 Oct 2021
FedChain: Chained Algorithms for Near-Optimal Communication Cost in Federated Learning Charlie Hou K. K. Thekumparampil Giulia Fanti Sewoong Oh FedML 30 14 0 16 Aug 2021
Local AdaGrad-Type Algorithm for Stochastic Convex-Concave Optimization Luofeng Liao Li Shen Jia Duan Mladen Kolar Dacheng Tao 11 4 0 18 Jun 2021
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities Aleksandr Beznosikov Pavel Dvurechensky Anastasia Koloskova V. Samokhin Sebastian U. Stich Alexander Gasnikov 24 43 0 15 Jun 2021
CDMA: A Practical Cross-Device Federated Learning Algorithm for General Minimax Problems Jiahao Xie Chao Zhang Zebang Shen Weijie Liu Hui Qian FedML 18 1 0 29 May 2021
On Solving Minimax Optimization Locally: A Follow-the-Ridge Approach Yuanhao Wang Guodong Zhang Jimmy Ba 31 100 0 16 Oct 2019
Linear Convergence of the Primal-Dual Gradient Method for Convex-Concave Saddle Point Problems without Strong Convexity S. Du Wei Hu 53 120 0 05 Feb 2018
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