A Unified and Refined Convergence Analysis for Non-Convex Decentralized Learning

19 October 2021

Papers citing "A Unified and Refined Convergence Analysis for Non-Convex Decentralized Learning"

35 / 35 papers shown

Title
Argus: Federated Non-convex Bilevel Learning over 6G Space-Air-Ground Integrated Network Ya Liu Kai Yang Yu Zhu Keying Yang Haibo Zhao 14 0 0 14 May 2025
Decentralized Nonconvex Composite Federated Learning with Gradient Tracking and Momentum Yuan Zhou Xinli Shi Xuelong Li Jiachen Zhong G. Wen Jinde Cao FedML 41 0 0 17 Apr 2025
Distributed Learning over Arbitrary Topology: Linear Speed-Up with Polynomial Transient Time Runze You Shi Pu 44 0 0 20 Mar 2025
A Bias-Correction Decentralized Stochastic Gradient Algorithm with Momentum Acceleration Yuchen Hu Xi Chen Weidong Liu Xiaojun Mao 57 0 0 31 Jan 2025
Generalization Error Matters in Decentralized Learning Under Byzantine Attacks Haoxiang Ye Qing Ling 37 0 0 11 Jul 2024
On the Trade-off between Flatness and Optimization in Distributed Learning Ying Cao Zhaoxian Wu Kun Yuan Ali H. Sayed 33 1 0 28 Jun 2024
Adjacent Leader Decentralized Stochastic Gradient Descent Haoze He Jing Wang A. Choromańska 22 0 0 18 May 2024
Convergence of Decentralized Stochastic Subgradient-based Methods for Nonsmooth Nonconvex functions Siyuan Zhang Nachuan Xiao Xin Liu 61 1 0 18 Mar 2024
An Accelerated Distributed Stochastic Gradient Method with Momentum Kun-Yen Huang Shi Pu Angelia Nedić 25 8 0 15 Feb 2024
Diffusion Stochastic Optimization for Min-Max Problems H. Cai Sulaiman A. Alghunaim Ali H. Sayed 24 2 0 26 Jan 2024
On the Communication Complexity of Decentralized Bilevel Optimization Yihan Zhang My T. Thai Jie Wu Hongchang Gao 20 3 0 19 Nov 2023
Locally Differentially Private Gradient Tracking for Distributed Online Learning over Directed Graphs Ziqin Chen Yongqiang Wang FedML 16 2 0 24 Oct 2023
Revisiting Decentralized ProxSkip: Achieving Linear Speedup Luyao Guo Sulaiman A. Alghunaim Kun Yuan Laurent Condat Jinde Cao FedML 36 1 0 12 Oct 2023
Online Distributed Learning with Quantized Finite-Time Coordination Nicola Bastianello Apostolos I. Rikos Karl H. Johansson FedML 14 2 0 13 Jul 2023
Momentum Benefits Non-IID Federated Learning Simply and Provably Ziheng Cheng Xinmeng Huang Pengfei Wu Kun Yuan FedML 29 16 0 28 Jun 2023
Distributed Random Reshuffling Methods with Improved Convergence Kun-Yen Huang Linli Zhou Shi Pu 24 4 0 21 Jun 2023
Optimized Gradient Tracking for Decentralized Online Learning Shivangi Sharma K. Rajawat 11 4 0 10 Jun 2023
DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm Lisang Ding Kexin Jin Bicheng Ying Kun Yuan W. Yin 6 9 0 01 Jun 2023
Unbiased Compression Saves Communication in Distributed Optimization: When and How Much? Yutong He Xinmeng Huang Kun Yuan 29 8 0 25 May 2023
Lower Bounds and Accelerated Algorithms in Distributed Stochastic Optimization with Communication Compression Yutong He Xinmeng Huang Yiming Chen W. Yin Kun Yuan 26 7 0 12 May 2023
Distributed Stochastic Optimization under a General Variance Condition Kun-Yen Huang Xiao Li Shin-Yi Pu FedML 37 5 0 30 Jan 2023
CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence Kun-Yen Huang Shin-Yi Pu 30 9 0 14 Jan 2023
Optimal Complexity in Non-Convex Decentralized Learning over Time-Varying Networks Xinmeng Huang Kun Yuan 22 6 0 01 Nov 2022
Communication-Efficient Topologies for Decentralized Learning with $O(1)$ Consensus Rate Zhuoqing Song Weijian Li Kexin Jin Lei Shi Ming Yan W. Yin Kun Yuan 6 31 0 14 Oct 2022
Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization Kun Yuan Xinmeng Huang Yiming Chen Xiaohan Zhang Yingya Zhang Pan Pan 16 17 0 14 Oct 2022
On the Performance of Gradient Tracking with Local Updates Edward Duc Hien Nguyen Sulaiman A. Alghunaim Kun Yuan César A. Uribe 35 18 0 10 Oct 2022
Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression Xinmeng Huang Yiming Chen W. Yin Kun Yuan 25 25 0 08 Jun 2022
Data-heterogeneity-aware Mixing for Decentralized Learning Yatin Dandi Anastasia Koloskova Martin Jaggi Sebastian U. Stich 23 18 0 13 Apr 2022
Distributed Random Reshuffling over Networks Kun-Yen Huang Xiao Li Andre Milzarek Shi Pu Junwen Qiu 34 11 0 31 Dec 2021
BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning Bicheng Ying Kun Yuan Hanbin Hu Yiming Chen W. Yin FedML 31 27 0 08 Nov 2021
Exponential Graph is Provably Efficient for Decentralized Deep Training Bicheng Ying Kun Yuan Yiming Chen Hanbin Hu Pan Pan W. Yin FedML 34 83 0 26 Oct 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
Removing Data Heterogeneity Influence Enhances Network Topology Dependence of Decentralized SGD Kun Yuan Sulaiman A. Alghunaim Xinmeng Huang 10 32 0 17 May 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
Distributed Pareto Optimization via Diffusion Strategies Jianshu Chen A. H. Sayed 55 174 0 13 Aug 2012