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Local SGD Converges Fast and Communicates Little

Local SGD Converges Fast and Communicates Little

24 May 2018
Sebastian U. Stich
    FedML
ArXivPDFHTML

Papers citing "Local SGD Converges Fast and Communicates Little"

50 / 629 papers shown
Title
Energy-Efficient Federated Learning for AIoT using Clustering Methods
Energy-Efficient Federated Learning for AIoT using Clustering Methods
Roberto Pereira
Fernanda Famá
Charalampos Kalalas
Paolo Dini
19
0
0
14 May 2025
Sharp Gaussian approximations for Decentralized Federated Learning
Sharp Gaussian approximations for Decentralized Federated Learning
Soham Bonnerjee
Sayar Karmakar
W. Wu
FedML
24
0
0
12 May 2025
Cluster-Aware Multi-Round Update for Wireless Federated Learning in Heterogeneous Environments
Cluster-Aware Multi-Round Update for Wireless Federated Learning in Heterogeneous Environments
Pengcheng Sun
Erwu Liu
Wei Ni
Kanglei Yu
Rui-cang Wang
Abbas Jamalipour
FedML
23
0
0
06 May 2025
Pseudo-Asynchronous Local SGD: Robust and Efficient Data-Parallel Training
Pseudo-Asynchronous Local SGD: Robust and Efficient Data-Parallel Training
Hiroki Naganuma
Xinzhi Zhang
Man-Chung Yue
Ioannis Mitliagkas
Philipp A. Witte
Russell J. Hewett
Yin Tat Lee
63
0
0
25 Apr 2025
A Tale of Two Learning Algorithms: Multiple Stream Random Walk and Asynchronous Gossip
A Tale of Two Learning Algorithms: Multiple Stream Random Walk and Asynchronous Gossip
Peyman Gholami
H. Seferoglu
29
0
0
14 Apr 2025
Federated Learning for Medical Image Classification: A Comprehensive Benchmark
Federated Learning for Medical Image Classification: A Comprehensive Benchmark
Zhekai Zhou
Guibo Luo
Mingzhi Chen
Zhenyu Weng
Yuesheng Zhu
FedML
26
0
0
07 Apr 2025
Client Selection in Federated Learning with Data Heterogeneity and Network Latencies
Client Selection in Federated Learning with Data Heterogeneity and Network Latencies
Harsh Vardhan
Xiaofan Yu
Tajana Rosing
A. Mazumdar
FedML
39
0
0
02 Apr 2025
Provable Reduction in Communication Rounds for Non-Smooth Convex Federated Learning
Provable Reduction in Communication Rounds for Non-Smooth Convex Federated Learning
Karlo Palenzuela
Ali Dadras
A. Yurtsever
Tommy Löfstedt
FedML
40
0
0
27 Mar 2025
From Interpretation to Correction: A Decentralized Optimization Framework for Exact Convergence in Federated Learning
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
Sense4FL: Vehicular Crowdsensing Enhanced Federated Learning for Autonomous Driving
Sense4FL: Vehicular Crowdsensing Enhanced Federated Learning for Autonomous Driving
Yanan Ma
Senkang Hu
Zhengru Fang
Yun Ji
Yiqin Deng
Yuguang Fang
46
0
0
22 Mar 2025
A Flexible Fairness Framework with Surrogate Loss Reweighting for Addressing Sociodemographic Disparities
A Flexible Fairness Framework with Surrogate Loss Reweighting for Addressing Sociodemographic Disparities
Wen Xu
Elham Dolatabadi
FaML
89
0
0
21 Mar 2025
Unified Analysis of Decentralized Gradient Descent: a Contraction Mapping Framework
Unified Analysis of Decentralized Gradient Descent: a Contraction Mapping Framework
Erik G. Larsson
Nicolo Michelusi
52
0
0
18 Mar 2025
Communication-Efficient Language Model Training Scales Reliably and Robustly: Scaling Laws for DiLoCo
Zachary B. Charles
Gabriel Teston
Lucio Dery
Keith Rush
Nova Fallen
Zachary Garrett
Arthur Szlam
Arthur Douillard
151
0
0
12 Mar 2025
Biased Federated Learning under Wireless Heterogeneity
Muhammad Faraz Ul Abrar
Nicolò Michelusi
FedML
44
0
0
08 Mar 2025
Convergence Analysis of Federated Learning Methods Using Backward Error Analysis
Jinwoo Lim
Suhyun Kim
Soo-Mook Moon
FedML
55
0
0
05 Mar 2025
Multi-Target Federated Backdoor Attack Based on Feature Aggregation
Multi-Target Federated Backdoor Attack Based on Feature Aggregation
Lingguag Hao
K. Hao
Bing Wei
Xue-song Tang
FedML
AAML
56
0
0
23 Feb 2025
Preconditioned Inexact Stochastic ADMM for Deep Model
Shenglong Zhou
Ouya Wang
Ziyan Luo
Yongxu Zhu
Geoffrey Ye Li
43
0
0
15 Feb 2025
Coreset-Based Task Selection for Sample-Efficient Meta-Reinforcement Learning
Coreset-Based Task Selection for Sample-Efficient Meta-Reinforcement Learning
Donglin Zhan
Leonardo F. Toso
James Anderson
97
1
0
04 Feb 2025
Communication-Efficient, 2D Parallel Stochastic Gradient Descent for Distributed-Memory Optimization
Communication-Efficient, 2D Parallel Stochastic Gradient Descent for Distributed-Memory Optimization
Aditya Devarakonda
Ramakrishnan Kannan
FedML
37
0
0
13 Jan 2025
Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis
Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis
Ruichen Luo
Sebastian U Stich
Samuel Horváth
Martin Takáč
38
0
0
08 Jan 2025
A Unified Analysis of Federated Learning with Arbitrary Client Participation
A Unified Analysis of Federated Learning with Arbitrary Client Participation
Shiqiang Wang
Mingyue Ji
FedML
37
55
0
31 Dec 2024
MARINA-P: Superior Performance in Non-smooth Federated Optimization with Adaptive Stepsizes
Igor Sokolov
Peter Richtárik
77
1
0
22 Dec 2024
Task Diversity in Bayesian Federated Learning: Simultaneous Processing
  of Classification and Regression
Task Diversity in Bayesian Federated Learning: Simultaneous Processing of Classification and Regression
Junliang Lyu
Yixuan Zhang
Xiaoling Lu
Feng Zhou
FedML
75
0
0
14 Dec 2024
Review of Mathematical Optimization in Federated Learning
Review of Mathematical Optimization in Federated Learning
Shusen Yang
Fangyuan Zhao
Zihao Zhou
Liang Shi
Xuebin Ren
Zongben Xu
FedML
AI4CE
70
0
0
02 Dec 2024
INTELLECT-1 Technical Report
INTELLECT-1 Technical Report
Sami Jaghouar
Jack Min Ong
Manveer Basra
Fares Obeid
Jannik Straube
...
Lucas Atkins
Maziyar Panahi
Charles Goddard
Max Ryabinin
Johannes Hagemann
MoE
65
1
0
02 Dec 2024
Hardware Scaling Trends and Diminishing Returns in Large-Scale Distributed Training
Hardware Scaling Trends and Diminishing Returns in Large-Scale Distributed Training
Jared Fernandez
Luca Wehrstedt
Leonid Shamis
Mostafa Elhoushi
Kalyan Saladi
Yonatan Bisk
Emma Strubell
Jacob Kahn
195
3
0
20 Nov 2024
Sketched Adaptive Federated Deep Learning: A Sharp Convergence Analysis
Sketched Adaptive Federated Deep Learning: A Sharp Convergence Analysis
Zhijie Chen
Qiaobo Li
A. Banerjee
FedML
35
0
0
11 Nov 2024
Photon: Federated LLM Pre-Training
Photon: Federated LLM Pre-Training
Lorenzo Sani
Alex Iacob
Zeyu Cao
Royson Lee
Bill Marino
...
Dongqi Cai
Zexi Li
Wanru Zhao
Xinchi Qiu
Nicholas D. Lane
AI4CE
26
7
0
05 Nov 2024
SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data
  Parallelism for LLM Training
SDP4Bit: Toward 4-bit Communication Quantization in Sharded Data Parallelism for LLM Training
Jinda Jia
Cong Xie
Hanlin Lu
Daoce Wang
Hao Feng
...
Baixi Sun
Haibin Lin
Zhi-Li Zhang
Xin Liu
Dingwen Tao
MQ
27
4
0
20 Oct 2024
Single-Timescale Multi-Sequence Stochastic Approximation Without Fixed
  Point Smoothness: Theories and Applications
Single-Timescale Multi-Sequence Stochastic Approximation Without Fixed Point Smoothness: Theories and Applications
Yue Huang
Zhaoxian Wu
Shiqian Ma
Qing Ling
31
1
0
17 Oct 2024
Glider: Global and Local Instruction-Driven Expert Router
Glider: Global and Local Instruction-Driven Expert Router
Pingzhi Li
Prateek Yadav
Jaehong Yoon
Jie Peng
Yi-Lin Sung
Mohit Bansal
Tianlong Chen
MoMe
MoE
27
1
0
09 Oct 2024
Communication-Efficient Federated Group Distributionally Robust
  Optimization
Communication-Efficient Federated Group Distributionally Robust Optimization
Zhishuai Guo
Tianbao Yang
FedML
30
0
0
08 Oct 2024
Aiding Global Convergence in Federated Learning via Local Perturbation
  and Mutual Similarity Information
Aiding Global Convergence in Federated Learning via Local Perturbation and Mutual Similarity Information
Emanuel Buttaci
Giuseppe Carlo Calafiore
FedML
24
0
0
07 Oct 2024
DEPT: Decoupled Embeddings for Pre-training Language Models
DEPT: Decoupled Embeddings for Pre-training Language Models
Alex Iacob
Lorenzo Sani
Meghdad Kurmanji
William F. Shen
Xinchi Qiu
Dongqi Cai
Yan Gao
Nicholas D. Lane
VLM
139
0
0
07 Oct 2024
No Need to Talk: Asynchronous Mixture of Language Models
No Need to Talk: Asynchronous Mixture of Language Models
Anastasiia Filippova
Angelos Katharopoulos
David Grangier
Ronan Collobert
MoE
36
0
0
04 Oct 2024
Collaborative and Efficient Personalization with Mixtures of Adaptors
Collaborative and Efficient Personalization with Mixtures of Adaptors
Abdulla Jasem Almansoori
Samuel Horváth
Martin Takáč
FedML
44
2
0
04 Oct 2024
Fine-Tuning Personalization in Federated Learning to Mitigate
  Adversarial Clients
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients
Youssef Allouah
Abdellah El Mrini
R. Guerraoui
Nirupam Gupta
Rafael Pinot
FedML
27
0
0
30 Sep 2024
Online Client Scheduling and Resource Allocation for Efficient Federated
  Edge Learning
Online Client Scheduling and Resource Allocation for Efficient Federated Edge Learning
Zhidong Gao
Zhenxiao Zhang
Yu Zhang
Tongnian Wang
Yanmin Gong
Yuanxiong Guo
30
0
0
29 Sep 2024
Hierarchical Federated Learning with Multi-Timescale Gradient Correction
Hierarchical Federated Learning with Multi-Timescale Gradient Correction
Wenzhi Fang
Dong-Jun Han
Evan Chen
Shiqiang Wang
Christopher G. Brinton
29
4
0
27 Sep 2024
Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in
  Unified Distributed SGD
Does Worst-Performing Agent Lead the Pack? Analyzing Agent Dynamics in Unified Distributed SGD
Jie Hu
Yi-Ting Ma
Do Young Eun
FedML
27
0
0
26 Sep 2024
Efficient Federated Learning against Heterogeneous and Non-stationary
  Client Unavailability
Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability
Ming Xiang
Stratis Ioannidis
Edmund Yeh
Carlee Joe-Wong
Lili Su
FedML
26
5
0
26 Sep 2024
Riemannian Federated Learning via Averaging Gradient Stream
Riemannian Federated Learning via Averaging Gradient Stream
Zhenwei Huang
Wen Huang
Pratik Jawanpuria
Bamdev Mishra
FedML
27
1
0
11 Sep 2024
SAB:A Stealing and Robust Backdoor Attack based on Steganographic
  Algorithm against Federated Learning
SAB:A Stealing and Robust Backdoor Attack based on Steganographic Algorithm against Federated Learning
Weida Xu
Yang Xu
Sicong Zhang
AAML
FedML
24
0
0
25 Aug 2024
Submodular Maximization Approaches for Equitable Client Selection in
  Federated Learning
Submodular Maximization Approaches for Equitable Client Selection in Federated Learning
Andrés Catalino Castillo Jiménez
Ege C. Kaya
Lintao Ye
Abolfazl Hashemi
FedML
49
2
0
24 Aug 2024
Understanding Data Reconstruction Leakage in Federated Learning from a
  Theoretical Perspective
Understanding Data Reconstruction Leakage in Federated Learning from a Theoretical Perspective
Zifan Wang
Binghui Zhang
Meng Pang
Yuan Hong
Binghui Wang
FedML
41
0
0
22 Aug 2024
Federated Frank-Wolfe Algorithm
Federated Frank-Wolfe Algorithm
Ali Dadras
Sourasekhar Banerjee
Karthik Prakhya
A. Yurtsever
FedML
32
4
0
19 Aug 2024
A Survey on Model MoErging: Recycling and Routing Among Specialized
  Experts for Collaborative Learning
A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning
Prateek Yadav
Colin Raffel
Mohammed Muqeeth
Lucas Page-Caccia
Haokun Liu
Tianlong Chen
Mohit Bansal
Leshem Choshen
Alessandro Sordoni
MoMe
43
21
0
13 Aug 2024
Rina: Enhancing Ring-AllReduce with In-network Aggregation in
  Distributed Model Training
Rina: Enhancing Ring-AllReduce with In-network Aggregation in Distributed Model Training
Zixuan Chen
Xuandong Liu
Minglin Li
Yinfan Hu
Hao Mei
Huifeng Xing
Hao Wang
Wanxin Shi
Sen Liu
Yang Xu
21
0
0
29 Jul 2024
FADAS: Towards Federated Adaptive Asynchronous Optimization
FADAS: Towards Federated Adaptive Asynchronous Optimization
Yujia Wang
Shiqiang Wang
Songtao Lu
Jinghui Chen
FedML
34
3
0
25 Jul 2024
Universally Harmonizing Differential Privacy Mechanisms for Federated
  Learning: Boosting Accuracy and Convergence
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence
Shuya Feng
Meisam Mohammady
Hanbin Hong
Shenao Yan
Ashish Kundu
Binghui Wang
Yuan Hong
FedML
38
3
0
20 Jul 2024
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