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Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data
International Conference on Machine Learning (ICML), 2021
9 February 2021
Tao Lin
Sai Praneeth Karimireddy
Sebastian U. Stich
Martin Jaggi
FedML
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Papers citing
"Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data"
50 / 71 papers shown
Unveiling the Power of Multiple Gossip Steps: A Stability-Based Generalization Analysis in Decentralized Training
Qinglun Li
Yingqi Liu
Miao Zhang
Xiaochun Cao
Quanjun Yin
Li Shen
161
2
0
09 Oct 2025
FedMuon: Federated Learning with Bias-corrected LMO-based Optimization
Yuki Takezawa
Anastasia Koloskova
Xiaowen Jiang
Sebastian U. Stich
196
0
0
30 Sep 2025
On the Surprising Effectiveness of a Single Global Merging in Decentralized Learning
Tongtian Zhu
Tianyu Zhang
Mingze Wang
Zhanpeng Zhou
Can Wang
FedML
399
0
0
09 Jul 2025
A Tale of Two Learning Algorithms: Multiple Stream Random Walk and Asynchronous Gossip
Peyman Gholami
H. Seferoglu
243
0
0
14 Apr 2025
PDSL: Privacy-Preserved Decentralized Stochastic Learning with Heterogeneous Data Distribution
IEEE International Conference on Distributed Computing Systems (ICDCS), 2025
Lina Wang
Yunsheng Yuan
Chunxiao Wang
Feng Li
FedML
477
1
0
31 Mar 2025
A Bias-Correction Decentralized Stochastic Gradient Algorithm with Momentum Acceleration
Yuchen Hu
Xi Chen
Weidong Liu
Xiaojun Mao
410
0
0
31 Jan 2025
Scalable Decentralized Learning with Teleportation
International Conference on Learning Representations (ICLR), 2025
Yuki Takezawa
Sebastian U. Stich
480
1
0
25 Jan 2025
ROSS: RObust decentralized Stochastic learning based on Shapley values
Lina Wang
Yunsheng Yuan
Feng Li
Lingjie Duan
FedML
385
0
0
01 Nov 2024
From promise to practice: realizing high-performance decentralized training
International Conference on Learning Representations (ICLR), 2024
Zesen Wang
Jiaojiao Zhang
Xuyang Wu
M. Johansson
370
3
0
15 Oct 2024
Ordered Momentum for Asynchronous SGD
Neural Information Processing Systems (NeurIPS), 2024
Chang-Wei Shi
Yi-Rui Yang
Wu-Jun Li
ODL
576
4
0
27 Jul 2024
Smart Sampling: Helping from Friendly Neighbors for Decentralized Federated Learning
Lin Wang
Yang Chen
Yongxin Guo
Xiaoying Tang
FedML
262
3
0
05 Jul 2024
Decentralized Directed Collaboration for Personalized Federated Learning
Yingqi Liu
Yifan Shi
Qinglun Li
Baoyuan Wu
Xueqian Wang
Li Shen
FedML
327
25
0
28 May 2024
SADDLe: Sharpness-Aware Decentralized Deep Learning with Heterogeneous Data
Sakshi Choudhary
Sai Aparna Aketi
Kaushik Roy
FedML
402
1
0
22 May 2024
DIMAT: Decentralized Iterative Merging-And-Training for Deep Learning Models
Nastaran Saadati
Minh Pham
Nasla Saleem
Joshua R. Waite
Aditya Balu
Zhanhong Jiang
Chinmay Hegde
Soumik Sarkar
MoMe
316
6
0
11 Apr 2024
AdaGossip: Adaptive Consensus Step-size for Decentralized Deep Learning with Communication Compression
Sai Aparna Aketi
Abolfazl Hashemi
Kaushik Roy
242
0
0
09 Apr 2024
FedNMUT -- Federated Noisy Model Update Tracking Convergence Analysis
Vishnu Pandi Chellapandi
Antesh Upadhyay
Abolfazl Hashemi
Stanislaw H. .Zak
FedML
344
4
0
20 Mar 2024
Averaging Rate Scheduler for Decentralized Learning on Heterogeneous Data
Sai Aparna Aketi
Sakshi Choudhary
Kaushik Roy
235
2
0
05 Mar 2024
An Accelerated Distributed Stochastic Gradient Method with Momentum
Kun-Yen Huang
Shi Pu
Angelia Nedić
421
15
0
15 Feb 2024
Decentralized Bilevel Optimization: A Perspective from Transient Iteration Complexity
Boao Kong
Shuchen Zhu
Songtao Lu
Xinmeng Huang
Kun Yuan
478
0
0
05 Feb 2024
DePRL: Achieving Linear Convergence Speedup in Personalized Decentralized Learning with Shared Representations
Efstathia Soufleri
Gang Yan
Maroun Touma
Jian Li
365
9
0
17 Dec 2023
Cross-feature Contrastive Loss for Decentralized Deep Learning on Heterogeneous Data
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2023
Sai Aparna Aketi
Kaushik Roy
FedML
377
3
0
24 Oct 2023
Asymmetrically Decentralized Federated Learning
IEEE transactions on computers (IEEE Trans. Comput.), 2023
Qinglun Li
Miao Zhang
Nan Yin
Quanjun Yin
Li Shen
FedML
395
8
0
08 Oct 2023
Efficient Federated Learning via Local Adaptive Amended Optimizer with Linear Speedup
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
Yan Sun
Li Shen
Hao Sun
Liang Ding
Dacheng Tao
FedML
200
35
0
30 Jul 2023
Achieving Linear Speedup in Decentralized Stochastic Compositional Minimax Optimization
Hongchang Gao
307
1
0
25 Jul 2023
Decentralized Local Updates with Dual-Slow Estimation and Momentum-based Variance-Reduction for Non-Convex Optimization
European Conference on Artificial Intelligence (ECAI), 2023
Kangyang Luo
Kunkun Zhang
Sheng Zhang
Xiang Li
Ming Gao
158
2
0
17 Jul 2023
Structured Cooperative Learning with Graphical Model Priors
International Conference on Machine Learning (ICML), 2023
Shuang-Yang Li
Wanrong Zhu
Xinmei Tian
Dacheng Tao
299
0
0
16 Jun 2023
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CiD
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CiD
2
: Accelerating Asynchronous Communication in Decentralized Deep Learning
Neural Information Processing Systems (NeurIPS), 2023
Adel Nabli
Eugene Belilovsky
Edouard Oyallon
378
10
0
14 Jun 2023
DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm
International Conference on Machine Learning (ICML), 2023
Lisang Ding
Kexin Jin
Bicheng Ying
Kun Yuan
W. Yin
280
12
0
01 Jun 2023
Unbiased Compression Saves Communication in Distributed Optimization: When and How Much?
Neural Information Processing Systems (NeurIPS), 2023
Yutong He
Xinmeng Huang
Kun Yuan
377
21
0
25 May 2023
Towards More Suitable Personalization in Federated Learning via Decentralized Partial Model Training
Yi Shi
Yingqi Liu
Yan Sun
Zihao Lin
Li Shen
Xueqian Wang
Dacheng Tao
FedML
343
13
0
24 May 2023
Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence
Neural Information Processing Systems (NeurIPS), 2023
Yuki Takezawa
Ryoma Sato
Han Bao
Kenta Niwa
M. Yamada
357
18
0
19 May 2023
Global Update Tracking: A Decentralized Learning Algorithm for Heterogeneous Data
Neural Information Processing Systems (NeurIPS), 2023
Sai Aparna Aketi
Abolfazl Hashemi
Kaushik Roy
FedML
241
17
0
08 May 2023
Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning
Deepak Ravikumar
Gobinda Saha
Sai Aparna Aketi
Kaushik Roy
276
5
0
09 Apr 2023
CoDeC: Communication-Efficient Decentralized Continual Learning
Sakshi Choudhary
Sai Aparna Aketi
Gobinda Saha
Kaushik Roy
CLL
241
5
0
27 Mar 2023
A Unified Momentum-based Paradigm of Decentralized SGD for Non-Convex Models and Heterogeneous Data
Haizhou Du
Chengdong Ni
183
3
0
01 Mar 2023
Beyond spectral gap (extended): The role of the topology in decentralized learning
Thijs Vogels
Aymeric Dieuleveut
Martin Jaggi
280
5
0
05 Jan 2023
Optimal Complexity in Non-Convex Decentralized Learning over Time-Varying Networks
Xinmeng Huang
Kun Yuan
239
9
0
01 Nov 2022
Aggregation in the Mirror Space (AIMS): Fast, Accurate Distributed Machine Learning in Military Settings
IEEE Military Communications Conference (MILCOM), 2022
Ryan Yang
Haizhou Du
Andre Wibisono
Patrick Baker
163
2
0
28 Oct 2022
Revisiting Optimal Convergence Rate for Smooth and Non-convex Stochastic Decentralized Optimization
Neural Information Processing Systems (NeurIPS), 2022
Kun Yuan
Xinmeng Huang
Yiming Chen
Xiaohan Zhang
Yingya Zhang
Pan Pan
293
33
0
14 Oct 2022
Depersonalized Federated Learning: Tackling Statistical Heterogeneity by Alternating Stochastic Gradient Descent
Yujie Zhou
Zhidu Li
Tong Tang
Ruyang Wang
FedML
333
0
0
07 Oct 2022
Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data
Yuki Takezawa
Hang Bao
Kenta Niwa
Ryoma Sato
Makoto Yamada
277
28
0
30 Sep 2022
Neighborhood Gradient Clustering: An Efficient Decentralized Learning Method for Non-IID Data Distributions
Sai Aparna Aketi
Sangamesh Kodge
Kaushik Roy
340
5
0
28 Sep 2022
On Generalization of Decentralized Learning with Separable Data
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Hossein Taheri
Christos Thrampoulidis
FedML
420
11
0
15 Sep 2022
Adaptive Step-Size Methods for Compressed SGD
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2022
Adarsh M. Subramaniam
A. Magesh
Venugopal V. Veeravalli
169
1
0
20 Jul 2022
TCT: Convexifying Federated Learning using Bootstrapped Neural Tangent Kernels
Neural Information Processing Systems (NeurIPS), 2022
Yaodong Yu
Alexander Wei
Sai Praneeth Karimireddy
Yi-An Ma
Michael I. Jordan
FedML
359
34
0
13 Jul 2022
Lower Bounds and Nearly Optimal Algorithms in Distributed Learning with Communication Compression
Neural Information Processing Systems (NeurIPS), 2022
Xinmeng Huang
Yiming Chen
W. Yin
Kun Yuan
422
41
0
08 Jun 2022
Beyond spectral gap: The role of the topology in decentralized learning
Neural Information Processing Systems (NeurIPS), 2022
Thijs Vogels
Aymeric Dieuleveut
Martin Jaggi
FedML
265
42
0
07 Jun 2022
DisPFL: Towards Communication-Efficient Personalized Federated Learning via Decentralized Sparse Training
International Conference on Machine Learning (ICML), 2022
Rong Dai
Li Shen
Fengxiang He
Xinmei Tian
Dacheng Tao
FedML
245
160
0
01 Jun 2022
Sign Bit is Enough: A Learning Synchronization Framework for Multi-hop All-reduce with Ultimate Compression
Design Automation Conference (DAC), 2022
Feijie Wu
Shiqi He
Song Guo
Zhihao Qu
Yining Qi
W. Zhuang
Jie Zhang
226
10
0
14 Apr 2022
Data-heterogeneity-aware Mixing for Decentralized Learning
Yatin Dandi
Anastasia Koloskova
Martin Jaggi
Sebastian U. Stich
280
22
0
13 Apr 2022
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