Federated Minimax Optimization: Improved Convergence Analyses and Algorithms

9 March 2022

Papers citing "Federated Minimax Optimization: Improved Convergence Analyses and Algorithms"

50 / 72 papers shown

Title
Robust Decentralized Learning with Local Updates and Gradient Tracking Sajjad Ghiasvand Amirhossein Reisizadeh Mahnoosh Alizadeh Ramtin Pedarsani 98 4 0 02 May 2024
Randomized Block-Coordinate Optimistic Gradient Algorithms for Root-Finding Problems Quoc Tran-Dinh Yang Luo 165 8 0 08 Jan 2023
Faster Single-loop Algorithms for Minimax Optimization without Strong Concavity Junchi Yang Antonio Orvieto Aurelien Lucchi Niao He 96 64 0 10 Dec 2021
FedMM: Saddle Point Optimization for Federated Adversarial Domain Adaptation Yan Shen Jianguo Du Hao Zhang Benyu Zhang Zhanghexuan Ji Mingchen Gao FedML 69 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 45 22 0 07 Oct 2021
Distributed Saddle-Point Problems Under Similarity Aleksandr Beznosikov G. Scutari Alexander Rogozin Alexander Gasnikov 67 15 0 22 Jul 2021
Decentralized Local Stochastic Extra-Gradient for Variational Inequalities Aleksandr Beznosikov Pavel Dvurechensky Anastasia Koloskova V. Samokhin Sebastian U. Stich Alexander Gasnikov 56 43 0 15 Jun 2021
Communication-efficient SGD: From Local SGD to One-Shot Averaging Artin Spiridonoff Alexander Olshevsky I. Paschalidis FedML 80 20 0 09 Jun 2021
Fast Federated Learning in the Presence of Arbitrary Device Unavailability Xinran Gu Kaixuan Huang Jingzhao Zhang Longbo Huang FedML 59 101 0 08 Jun 2021
Near Optimal Stochastic Algorithms for Finite-Sum Unbalanced Convex-Concave Minimax Optimization Luo Luo Guangzeng Xie Tong Zhang Zhihua Zhang 57 19 0 03 Jun 2021
Stability and Generalization of Stochastic Gradient Methods for Minimax Problems Yunwen Lei Zhenhuan Yang Tianbao Yang Yiming Ying 63 48 0 08 May 2021
Complexity Lower Bounds for Nonconvex-Strongly-Concave Min-Max Optimization Haochuan Li Yi Tian Jingzhao Zhang Ali Jadbabaie 68 41 0 18 Apr 2021
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization Siqi Zhang Junchi Yang Cristóbal Guzmán Negar Kiyavash Niao He 68 62 0 29 Mar 2021
Local Stochastic Gradient Descent Ascent: Convergence Analysis and Communication Efficiency Yuyang Deng M. Mahdavi 91 61 0 25 Feb 2021
Distributionally Robust Federated Averaging Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 48 142 0 25 Feb 2021
Decentralized Distributed Optimization for Saddle Point Problems Alexander Rogozin Alexander Beznosikov D. Dvinskikh D. Kovalev Pavel Dvurechensky Alexander Gasnikov 77 27 0 15 Feb 2021
Efficient Algorithms for Federated Saddle Point Optimization Charlie Hou K. K. Thekumparampil Giulia Fanti Sewoong Oh FedML 86 23 0 12 Feb 2021
Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry Ziyi Chen Yi Zhou Tengyu Xu Yingbin Liang 104 35 0 09 Feb 2021
Federated Deep AUC Maximization for Heterogeneous Data with a Constant Communication Complexity Zhuoning Yuan Zhishuai Guo Yi Tian Xu Yiming Ying Tianbao Yang FedML 61 36 0 09 Feb 2021
Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning Haibo Yang Minghong Fang Jia Liu FedML 66 258 0 27 Jan 2021
Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization Jelena Diakonikolas C. Daskalakis Michael I. Jordan 75 144 0 31 Oct 2020
A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems Jiawei Zhang Peijun Xiao Ruoyu Sun Zhi-Quan Luo 110 99 0 29 Oct 2020
A Distributed Training Algorithm of Generative Adversarial Networks with Quantized Gradients Xiaojun Chen Shu Yang Liyan Shen Xuanrong Pang 28 4 0 26 Oct 2020
On The Convergence of First Order Methods for Quasar-Convex Optimization Jikai Jin 49 9 0 10 Oct 2020
The Complexity of Constrained Min-Max Optimization C. Daskalakis Stratis Skoulakis Manolis Zampetakis 115 137 0 21 Sep 2020
Single-Timescale Stochastic Nonconvex-Concave Optimization for Smooth Nonlinear TD Learning Shuang Qiu Zhuoran Yang Xiaohan Wei Jieping Ye Zhaoran Wang 81 38 0 23 Aug 2020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization Jianyu Wang Qinghua Liu Hao Liang Gauri Joshi H. Vincent Poor MoMe FedML 68 1,337 0 15 Jul 2020
The limits of min-max optimization algorithms: convergence to spurious non-critical sets Ya-Ping Hsieh P. Mertikopoulos Volkan Cevher 80 83 0 16 Jun 2020
Robust Federated Learning: The Case of Affine Distribution Shifts Amirhossein Reisizadeh Farzan Farnia Ramtin Pedarsani Ali Jadbabaie FedML OOD 85 164 0 16 Jun 2020
Improved Algorithms for Convex-Concave Minimax Optimization Yuanhao Wang Jian Li 64 64 0 11 Jun 2020
A Unified Single-loop Alternating Gradient Projection Algorithm for Nonconvex-Concave and Convex-Nonconcave Minimax Problems Zi Xu Hui-Li Zhang Yang Xu Guanghui Lan 72 100 0 03 Jun 2020
Communication-Efficient Distributed Stochastic AUC Maximization with Deep Neural Networks Zhishuai Guo Mingrui Liu Zhuoning Yuan Li Shen Wei Liu Tianbao Yang 65 42 0 05 May 2020
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates Anastasia Koloskova Nicolas Loizou Sadra Boreiri Martin Jaggi Sebastian U. Stich FedML 85 506 0 23 Mar 2020
Loss landscapes and optimization in over-parameterized non-linear systems and neural networks Chaoyue Liu Libin Zhu M. Belkin ODL 77 262 0 29 Feb 2020
Federated Learning with Matched Averaging Hongyi Wang Mikhail Yurochkin Yuekai Sun Dimitris Papailiopoulos Y. Khazaeni FedML 121 1,124 0 15 Feb 2020
Near-Optimal Algorithms for Minimax Optimization Tianyi Lin Chi Jin Michael I. Jordan 159 254 0 05 Feb 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 259 6,261 0 10 Dec 2019
Lower Bounds for Non-Convex Stochastic Optimization Yossi Arjevani Y. Carmon John C. Duchi Dylan J. Foster Nathan Srebro Blake E. Woodworth 81 361 0 05 Dec 2019
On the Convergence of Local Descent Methods in Federated Learning Farzin Haddadpour M. Mahdavi FedML 81 273 0 31 Oct 2019
A Decentralized Proximal Point-type Method for Saddle Point Problems Weijie Liu Aryan Mokhtari Asuman Ozdaglar S. Pattathil Zebang Shen Nenggan Zheng 107 30 0 31 Oct 2019
A Decentralized Parallel Algorithm for Training Generative Adversarial Nets Mingrui Liu Wei Zhang Youssef Mroueh Xiaodong Cui Jerret Ross Tianbao Yang Payel Das 48 74 0 28 Oct 2019
Tighter Theory for Local SGD on Identical and Heterogeneous Data Ahmed Khaled Konstantin Mishchenko Peter Richtárik 74 433 0 10 Sep 2019
Efficient Algorithms for Smooth Minimax Optimization K. K. Thekumparampil Prateek Jain Praneeth Netrapalli Sewoong Oh 89 191 0 02 Jul 2019
Near-Optimal Methods for Minimizing Star-Convex Functions and Beyond Oliver Hinder Aaron Sidford N. Sohoni 47 71 0 27 Jun 2019
Adversarial Attack Generation Empowered by Min-Max Optimization Jingkang Wang Tianyun Zhang Sijia Liu Pin-Yu Chen Jiacen Xu M. Fardad Yangqiu Song AAML 53 37 0 09 Jun 2019
On Gradient Descent Ascent for Nonconvex-Concave Minimax Problems Tianyi Lin Chi Jin Michael I. Jordan 126 507 0 02 Jun 2019
On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization Hao Yu Rong Jin Sen Yang FedML 91 384 0 09 May 2019
Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods Maher Nouiehed Maziar Sanjabi Tianjian Huang Jason D. Lee Meisam Razaviyayn 82 344 0 21 Feb 2019
Hybrid Block Successive Approximation for One-Sided Non-Convex Min-Max Problems: Algorithms and Applications Songtao Lu Ioannis C. Tsaknakis Mingyi Hong Yongxin Chen 69 170 0 21 Feb 2019
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 121 2,666 0 04 Feb 2019