Exponential Graph is Provably Efficient for Decentralized Deep Training

Exponential Graph is Provably Efficient for Decentralized Deep Training

26 October 2021

Papers citing "Exponential Graph is Provably Efficient for Decentralized Deep Training"

12 / 12 papers shown

Title
From Interpretation to Correction: A Decentralized Optimization Framework for Exact Convergence in Federated Learning Bicheng Ying Zhe Li Haibo Yang FedML 68 0 0 25 Mar 2025
Scalable Decentralized Learning with Teleportation Yuki Takezawa Sebastian U. Stich 54 1 0 25 Jan 2025
OledFL: Unleashing the Potential of Decentralized Federated Learning via Opposite Lookahead Enhancement Qinglun Li Miao Zhang Mengzhu Wang Quanjun Yin Li Shen OODD FedML 14 0 0 09 Oct 2024
Rate Analysis of Coupled Distributed Stochastic Approximation for Misspecified Optimization Yaqun Yang Jinlong Lei 19 0 0 21 Apr 2024
Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence Yuki Takezawa Ryoma Sato Han Bao Kenta Niwa M. Yamada 24 9 0 19 May 2023
Decentralized Learning Made Practical with Client Sampling M. Vos Akash Dhasade Anne-Marie Kermarrec Erick Lavoie J. Pouwelse Rishi Sharma 16 1 0 27 Feb 2023
Decentralized Stochastic Gradient Descent Ascent for Finite-Sum Minimax Problems Hongchang Gao 16 16 0 06 Dec 2022
Secure Distributed Optimization Under Gradient Attacks Shuhua Yu S. Kar 22 13 0 28 Oct 2022
Byzantine-Resilient Decentralized Stochastic Optimization with Robust Aggregation Rules Zhaoxian Wu Tianyi Chen Qing Ling 26 36 0 09 Jun 2022
Heavy-Tail Phenomenon in Decentralized SGD Mert Gurbuzbalaban Yuanhan Hu Umut Simsekli Kun Yuan Lingjiong Zhu 19 8 0 13 May 2022
BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning Bicheng Ying Kun Yuan Hanbin Hu Yiming Chen W. Yin FedML 29 27 0 08 Nov 2021
DecentLaM: Decentralized Momentum SGD for Large-batch Deep Training Kun Yuan Yiming Chen Xinmeng Huang Yingya Zhang Pan Pan Yinghui Xu W. Yin MoE 46 60 0 24 Apr 2021