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1805.09767
Cited By
Local SGD Converges Fast and Communicates Little
24 May 2018
Sebastian U. Stich
FedML
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Papers citing
"Local SGD Converges Fast and Communicates Little"
50 / 631 papers shown
Title
Personalized Federated Learning with Multiple Known Clusters
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3
0
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On the Convergence of Momentum-Based Algorithms for Federated Bilevel Optimization Problems
Hongchang Gao
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49
1
0
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AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation
Farshid Varno
Marzie Saghayi
Laya Rafiee
Sharut Gupta
Stan Matwin
Mohammad Havaei
FedML
34
30
0
27 Apr 2022
FedShuffle: Recipes for Better Use of Local Work in Federated Learning
Samuel Horváth
Maziar Sanjabi
Lin Xiao
Peter Richtárik
Michael G. Rabbat
FedML
33
21
0
27 Apr 2022
Federated Learning via Inexact ADMM
Shenglong Zhou
Geoffrey Ye Li
FedML
24
59
0
22 Apr 2022
FedCorr: Multi-Stage Federated Learning for Label Noise Correction
Jingyi Xu
Zihan Chen
Tony Q.S. Quek
Kai Fong Ernest Chong
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24
85
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10 Apr 2022
FedADMM: A Robust Federated Deep Learning Framework with Adaptivity to System Heterogeneity
Yonghai Gong
Yichuan Li
N. Freris
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16
45
0
07 Apr 2022
FedADMM: A Federated Primal-Dual Algorithm Allowing Partial Participation
Han Wang
Siddartha Marella
James Anderson
FedML
14
39
0
28 Mar 2022
SlimFL: Federated Learning with Superposition Coding over Slimmable Neural Networks
Won Joon Yun
Yunseok Kwak
Hankyul Baek
Soyi Jung
Mingyue Ji
M. Bennis
Jihong Park
Joongheon Kim
23
16
0
26 Mar 2022
Local Stochastic Factored Gradient Descent for Distributed Quantum State Tomography
J. Kim
Taha Toghani
César A. Uribe
Anastasios Kyrillidis
35
3
0
22 Mar 2022
The Role of Local Steps in Local SGD
Tiancheng Qin
S. Rasoul Etesami
César A. Uribe
21
4
0
14 Mar 2022
Scaling the Wild: Decentralizing Hogwild!-style Shared-memory SGD
Bapi Chatterjee
Vyacheslav Kungurtsev
Dan Alistarh
FedML
27
2
0
13 Mar 2022
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms
Pranay Sharma
Rohan Panda
Gauri Joshi
P. Varshney
FedML
21
47
0
09 Mar 2022
BagPipe: Accelerating Deep Recommendation Model Training
Saurabh Agarwal
Chengpo Yan
Ziyi Zhang
Shivaram Venkataraman
37
18
0
24 Feb 2022
FedCAT: Towards Accurate Federated Learning via Device Concatenation
Ming Hu
Tian Liu
Zhiwei Ling
Zhihao Yue
Mingsong Chen
FedML
24
1
0
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ProxSkip: Yes! Local Gradient Steps Provably Lead to Communication Acceleration! Finally!
Konstantin Mishchenko
Grigory Malinovsky
Sebastian U. Stich
Peter Richtárik
11
152
0
18 Feb 2022
On the Convergence of Clustered Federated Learning
Ma Jie
Guodong Long
Dinesh Manocha
Jing Jiang
Chengqi Zhang
FedML
39
46
0
13 Feb 2022
On Federated Learning with Energy Harvesting Clients
Cong Shen
Jing Yang
Jie Xu
FedML
30
6
0
12 Feb 2022
Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning
Tomoya Murata
Taiji Suzuki
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6
3
0
12 Feb 2022
Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam
Yucheng Lu
Conglong Li
Minjia Zhang
Christopher De Sa
Yuxiong He
OffRL
AI4CE
26
20
0
12 Feb 2022
Comparative assessment of federated and centralized machine learning
Ibrahim Abdul Majeed
Sagar Kaushik
Aniruddha Bardhan
Venkata Siva Kumar Tadi
Hwang-Ki Min
K. Kumaraguru
Rajasekhara Reddy Duvvuru Muni
FedML
31
6
0
03 Feb 2022
3PC: Three Point Compressors for Communication-Efficient Distributed Training and a Better Theory for Lazy Aggregation
Peter Richtárik
Igor Sokolov
Ilyas Fatkhullin
Elnur Gasanov
Zhize Li
Eduard A. Gorbunov
23
31
0
02 Feb 2022
Recycling Model Updates in Federated Learning: Are Gradient Subspaces Low-Rank?
Sheikh Shams Azam
Seyyedali Hosseinalipour
Qiang Qiu
Christopher G. Brinton
FedML
26
20
0
01 Feb 2022
Faster Convergence of Local SGD for Over-Parameterized Models
Tiancheng Qin
S. Rasoul Etesami
César A. Uribe
FedML
38
6
0
30 Jan 2022
Gradient Masked Averaging for Federated Learning
Irene Tenison
Sai Aravind Sreeramadas
Vaikkunth Mugunthan
Edouard Oyallon
Irina Rish
Eugene Belilovsky
FedML
68
24
0
28 Jan 2022
On the Convergence of Heterogeneous Federated Learning with Arbitrary Adaptive Online Model Pruning
Hanhan Zhou
Tian-Shing Lan
Guru Venkataramani
Wenbo Ding
FedML
32
6
0
27 Jan 2022
Achieving Personalized Federated Learning with Sparse Local Models
Tiansheng Huang
Shiwei Liu
Li Shen
Fengxiang He
Weiwei Lin
Dacheng Tao
FedML
30
43
0
27 Jan 2022
Federated Learning with Heterogeneous Architectures using Graph HyperNetworks
Or Litany
Haggai Maron
David Acuna
Jan Kautz
Gal Chechik
Sanja Fidler
FedML
40
24
0
20 Jan 2022
Variance-Reduced Heterogeneous Federated Learning via Stratified Client Selection
Guangyuan Shen
D. Gao
Libin Yang
Fang Zhou
Duanxiao Song
Wei Lou
Shirui Pan
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19
8
0
15 Jan 2022
Partial Model Averaging in Federated Learning: Performance Guarantees and Benefits
Sunwoo Lee
Anit Kumar Sahu
Chaoyang He
Salman Avestimehr
FedML
33
17
0
11 Jan 2022
Communication-Efficient Federated Learning with Accelerated Client Gradient
Geeho Kim
Jinkyu Kim
Bohyung Han
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40
11
0
10 Jan 2022
AET-SGD: Asynchronous Event-triggered Stochastic Gradient Descent
Nhuong V. Nguyen
Song Han
21
2
0
27 Dec 2021
Automatic Configuration for Optimal Communication Scheduling in DNN Training
Yiqing Ma
Hao Wang
Yiming Zhang
Kai Chen
22
12
0
27 Dec 2021
Towards Federated Learning on Time-Evolving Heterogeneous Data
Yongxin Guo
Tao R. Lin
Xiaoying Tang
FedML
22
30
0
25 Dec 2021
Sparsified Secure Aggregation for Privacy-Preserving Federated Learning
Irem Ergun
Hasin Us Sami
Başak Güler
FedML
46
26
0
23 Dec 2021
FedLGA: Towards System-Heterogeneity of Federated Learning via Local Gradient Approximation
Xingyu Li
Zhe Qu
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Zhuo Lu
FedML
33
25
0
22 Dec 2021
Tackling System and Statistical Heterogeneity for Federated Learning with Adaptive Client Sampling
Bing Luo
Wenli Xiao
Shiqiang Wang
Jianwei Huang
Leandros Tassiulas
FedML
42
168
0
21 Dec 2021
From Deterioration to Acceleration: A Calibration Approach to Rehabilitating Step Asynchronism in Federated Optimization
Feijie Wu
Song Guo
Yining Qi
Zhihao Qu
Haobo Zhang
Jiewei Zhang
Ziming Liu
25
11
0
17 Dec 2021
LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization
Huiming Chen
Huandong Wang
Quanming Yao
Yong Li
Depeng Jin
Qiang Yang
FedML
27
4
0
15 Dec 2021
Communication-Efficient Distributed SGD with Compressed Sensing
Yujie Tang
V. Ramanathan
Junshan Zhang
Na Li
FedML
33
8
0
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SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification
Ashwinee Panda
Saeed Mahloujifar
A. Bhagoji
Supriyo Chakraborty
Prateek Mittal
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0
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On Convergence of Federated Averaging Langevin Dynamics
Wei Deng
Qian Zhang
Yi Ma
Zhao Song
Guang Lin
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30
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0
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Communication-Efficient Distributed Learning via Sparse and Adaptive Stochastic Gradient
Xiaoge Deng
Dongsheng Li
Tao Sun
Xicheng Lu
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26
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Collaborative Learning over Wireless Networks: An Introductory Overview
Emre Ozfatura
Deniz Gunduz
H. Vincent Poor
30
11
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On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons
Fangshuo Liao
Anastasios Kyrillidis
51
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0
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Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks
Hankyul Baek
Won Joon Yun
Yunseok Kwak
Soyi Jung
Mingyue Ji
M. Bennis
Jihong Park
Joongheon Kim
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74
22
0
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Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks
M. Ramezani
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Mehrdad Mahdavi
M. Kandemir
A. Sivasubramaniam
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Persia: An Open, Hybrid System Scaling Deep Learning-based Recommenders up to 100 Trillion Parameters
Xiangru Lian
Binhang Yuan
Xuefeng Zhu
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Ce Zhang
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34
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BlueFog: Make Decentralized Algorithms Practical for Optimization and Deep Learning
Bicheng Ying
Kun Yuan
Hanbin Hu
Yiming Chen
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39
27
0
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Federated Learning Based on Dynamic Regularization
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Ramon Matas Navarro
Matthew Mattina
P. Whatmough
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750
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