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A Unified Analysis of Federated Learning with Arbitrary Client Participation

A Unified Analysis of Federated Learning with Arbitrary Client Participation

31 December 2024
Shiqiang Wang
Mingyue Ji
    FedML
ArXivPDFHTML

Papers citing "A Unified Analysis of Federated Learning with Arbitrary Client Participation"

13 / 63 papers shown
Title
On the Convergence of FedAvg on Non-IID Data
On the Convergence of FedAvg on Non-IID Data
Xiang Li
Kaixuan Huang
Wenhao Yang
Shusen Wang
Zhihua Zhang
FedML
138
2,327
0
04 Jul 2019
On the Linear Speedup Analysis of Communication Efficient Momentum SGD
  for Distributed Non-Convex Optimization
On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization
Hao Yu
Rong Jin
Sen Yang
FedML
78
384
0
09 May 2019
Semi-Cyclic Stochastic Gradient Descent
Semi-Cyclic Stochastic Gradient Descent
Hubert Eichner
Tomer Koren
H. B. McMahan
Nathan Srebro
Kunal Talwar
73
108
0
23 Apr 2019
Towards Federated Learning at Scale: System Design
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
119
2,660
0
04 Feb 2019
SGD: General Analysis and Improved Rates
SGD: General Analysis and Improved Rates
Robert Mansel Gower
Nicolas Loizou
Xun Qian
Alibek Sailanbayev
Egor Shulgin
Peter Richtárik
68
379
0
27 Jan 2019
Federated Optimization in Heterogeneous Networks
Federated Optimization in Heterogeneous Networks
Tian Li
Anit Kumar Sahu
Manzil Zaheer
Maziar Sanjabi
Ameet Talwalkar
Virginia Smith
FedML
173
5,148
0
14 Dec 2018
Adaptive Communication Strategies to Achieve the Best Error-Runtime
  Trade-off in Local-Update SGD
Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD
Jianyu Wang
Gauri Joshi
FedML
65
232
0
19 Oct 2018
Don't Use Large Mini-Batches, Use Local SGD
Don't Use Large Mini-Batches, Use Local SGD
Tao R. Lin
Sebastian U. Stich
Kumar Kshitij Patel
Martin Jaggi
111
433
0
22 Aug 2018
Parallel Restarted SGD with Faster Convergence and Less Communication:
  Demystifying Why Model Averaging Works for Deep Learning
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning
Hao Yu
Sen Yang
Shenghuo Zhu
MoMe
FedML
73
604
0
17 Jul 2018
Local SGD Converges Fast and Communicates Little
Local SGD Converges Fast and Communicates Little
Sebastian U. Stich
FedML
164
1,061
0
24 May 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning
  Algorithms
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms
Han Xiao
Kashif Rasul
Roland Vollgraf
246
8,856
0
25 Aug 2017
Communication-Efficient Learning of Deep Networks from Decentralized
  Data
Communication-Efficient Learning of Deep Networks from Decentralized Data
H. B. McMahan
Eider Moore
Daniel Ramage
S. Hampson
Blaise Agüera y Arcas
FedML
380
17,437
0
17 Feb 2016
Delving Deep into Rectifiers: Surpassing Human-Level Performance on
  ImageNet Classification
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
VLM
280
18,587
0
06 Feb 2015
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