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1705.09056
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Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent
25 May 2017
Xiangru Lian
Ce Zhang
Huan Zhang
Cho-Jui Hsieh
Wei Zhang
Ji Liu
Re-assign community
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Papers citing
"Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descent"
50 / 627 papers shown
Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm
International Conference on Machine Learning (ICML), 2023
B. L. Bars
A. Bellet
Marc Tommasi
Kevin Scaman
Giovanni Neglia
380
10
0
05 Jun 2023
Decentralized SGD and Average-direction SAM are Asymptotically Equivalent
International Conference on Machine Learning (ICML), 2023
Tongtian Zhu
Fengxiang He
Kaixuan Chen
Weilong Dai
Dacheng Tao
664
20
0
05 Jun 2023
When Decentralized Optimization Meets Federated Learning
IEEE Network (IEEE Netw.), 2023
Hongchang Gao
My T. Thai
Jie Wu
FedML
232
28
0
05 Jun 2023
Decentralized Federated Learning: A Survey and Perspective
IEEE Internet of Things Journal (IEEE IoT J.), 2023
Liangqi Yuan
Ziran Wang
Lichao Sun
Philip S. Yu
Christopher G. Brinton
FedML
311
220
0
02 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
199
11
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
317
19
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
241
13
0
24 May 2023
On the Optimal Batch Size for Byzantine-Robust Distributed Learning
Yi-Rui Yang
Chang-Wei Shi
Wu-Jun Li
FedML
AAML
261
1
0
23 May 2023
Distributed Learning over Networks with Graph-Attention-Based Personalization
IEEE Transactions on Signal Processing (IEEE TSP), 2023
Zhuojun Tian
Zhaoyang Zhang
Zhaohui Yang
Richeng Jin
H. Dai
GNN
FedML
203
11
0
22 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
277
16
0
19 May 2023
Convergence and Privacy of Decentralized Nonconvex Optimization with Gradient Clipping and Communication Compression
IEEE Journal on Selected Topics in Signal Processing (JSTSP), 2023
Boyue Li
Yuejie Chi
178
18
0
17 May 2023
Understanding and Improving Model Averaging in Federated Learning on Heterogeneous Data
IEEE Transactions on Mobile Computing (IEEE TMC), 2023
Tailin Zhou
Zehong Lin
Jinchao Zhang
Danny H. K. Tsang
MoMe
FedML
400
23
0
13 May 2023
Decentralized Learning over Wireless Networks: The Effect of Broadcast with Random Access
International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2023
Zheng Chen
Martin Dahl
Erik G. Larsson
276
6
0
12 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
186
16
0
08 May 2023
Attacks on Robust Distributed Learning Schemes via Sensitivity Curve Maximization
International Conference on Digital Signal Processing (ICDSP), 2023
Christian A. Schroth
Stefan Vlaski
A. Zoubir
FedML
197
2
0
27 Apr 2023
Can Decentralized Stochastic Minimax Optimization Algorithms Converge Linearly for Finite-Sum Nonconvex-Nonconcave Problems?
Yihan Zhang
Wenhao Jiang
Feng-Song Zheng
C. C. Tan
Xinghua Shi
Hongchang Gao
150
1
0
24 Apr 2023
Near-Optimal Decentralized Momentum Method for Nonconvex-PL Minimax Problems
Feihu Huang
Songcan Chen
185
8
0
21 Apr 2023
Joint Client Assignment and UAV Route Planning for Indirect-Communication Federated Learning
Jieming Bian
Cong Shen
Jie Xu
FedML
249
3
0
21 Apr 2023
Decentralized Learning Made Easy with DecentralizePy
Akash Dhasade
Anne-Marie Kermarrec
Rafael Pires
Rishi Sharma
Milos Vujasinovic
182
21
0
17 Apr 2023
Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis
Neural Information Processing Systems (NeurIPS), 2023
Dachao Lin
Yuze Han
Haishan Ye
Zhihua Zhang
319
15
0
15 Apr 2023
Exact Subspace Diffusion for Decentralized Multitask Learning
IEEE Conference on Decision and Control (CDC), 2023
Shreya Wadehra
Roula Nassif
Stefan Vlaski
160
2
0
14 Apr 2023
Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning
Deepak Ravikumar
Gobinda Saha
Sai Aparna Aketi
Kaushik Roy
244
5
0
09 Apr 2023
CoDeC: Communication-Efficient Decentralized Continual Learning
Sakshi Choudhary
Sai Aparna Aketi
Gobinda Saha
Kaushik Roy
CLL
208
4
0
27 Mar 2023
Communication-Efficient Design for Quantized Decentralized Federated Learning
IEEE Transactions on Signal Processing (IEEE TSP), 2023
Lixing Chen
Wei Liu
Yunfei Chen
Weidong Wang
FedML
MQ
283
23
0
15 Mar 2023
Comparative Evaluation of Data Decoupling Techniques for Federated Machine Learning with Database as a Service
Muhammad Jahanzeb Khan
Rui Hu
Mohammad Sadoghi
Dongfang Zhao
FedML
105
0
0
15 Mar 2023
Cloudless-Training: A Framework to Improve Efficiency of Geo-Distributed ML Training
W. Tan
Xiao Shi
Cunchi Lv
Xiaofang Zhao
FedML
134
1
0
09 Mar 2023
FedREP: A Byzantine-Robust, Communication-Efficient and Privacy-Preserving Framework for Federated Learning
Yi-Rui Yang
Kun Wang
Wulu Li
FedML
245
6
0
09 Mar 2023
Can Decentralized Learning be more robust than Federated Learning?
Mathilde Raynal
Dario Pasquini
Carmela Troncoso
OOD
FedML
300
5
0
07 Mar 2023
PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities
ACM Interational Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 2023
Zhuqing Liu
Xin Zhang
Songtao Lu
Jia-Wei Liu
198
8
0
05 Mar 2023
A Unified Momentum-based Paradigm of Decentralized SGD for Non-Convex Models and Heterogeneous Data
Haizhou Du
Chengdong Ni
133
3
0
01 Mar 2023
Decentralized Learning Made Practical with Client Sampling
M. Vos
Akash Dhasade
Anne-Marie Kermarrec
Erick Lavoie
J. Pouwelse
Rishi Sharma
270
1
0
27 Feb 2023
P4L: Privacy Preserving Peer-to-Peer Learning for Infrastructureless Setups
Ioannis Arapakis
P. Papadopoulos
Kleomenis Katevas
Diego Perino
145
10
0
26 Feb 2023
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning
International Conference on Machine Learning (ICML), 2023
Edwige Cyffers
A. Bellet
D. Basu
FedML
370
5
0
24 Feb 2023
A One-Sample Decentralized Proximal Algorithm for Non-Convex Stochastic Composite Optimization
Conference on Uncertainty in Artificial Intelligence (UAI), 2023
Tesi Xiao
Xuxing Chen
Krishnakumar Balasubramanian
Saeed Ghadimi
253
13
0
20 Feb 2023
Improving the Model Consistency of Decentralized Federated Learning
International Conference on Machine Learning (ICML), 2023
Yi Shi
Li Shen
Kang Wei
Yan Sun
Bo Yuan
Xueqian Wang
Dacheng Tao
FedML
259
73
0
08 Feb 2023
Decentralized Riemannian Algorithm for Nonconvex Minimax Problems
AAAI Conference on Artificial Intelligence (AAAI), 2023
Xidong Wu
Zhengmian Hu
Heng Huang
422
15
0
08 Feb 2023
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-SignFedAvg: A Unified Stochastic Sign-based Compression for Federated Learning
AAAI Conference on Artificial Intelligence (AAAI), 2023
Zhiwei Tang
Yanmeng Wang
Tsung-Hui Chang
FedML
293
23
0
06 Feb 2023
Topology-aware Federated Learning in Edge Computing: A Comprehensive Survey
ACM Computing Surveys (ACM Comput. Surv.), 2023
Jiajun Wu
Steve Drew
Fan Dong
Zhuangdi Zhu
Jiayu Zhou
FedML
323
98
0
06 Feb 2023
Efficient Node Selection in Private Personalized Decentralized Learning
Edvin Listo Zec
Johan Ostman
Olof Mogren
D. Gillblad
223
1
0
30 Jan 2023
Delayed Stochastic Algorithms for Distributed Weakly Convex Optimization
W. Gao
Qinhao Deng
344
0
0
30 Jan 2023
Distributed Stochastic Optimization under a General Variance Condition
IEEE Transactions on Automatic Control (TAC), 2023
Kun-Yen Huang
Xiao Li
Shin-Yi Pu
FedML
365
12
0
30 Jan 2023
SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient
International Conference on Machine Learning (ICML), 2023
Max Ryabinin
Tim Dettmers
Michael Diskin
Alexander Borzunov
MoE
378
57
0
27 Jan 2023
Distributed Optimization Methods for Multi-Robot Systems: Part II -- A Survey
IEEE robotics & automation magazine (IEEE RAM), 2023
O. Shorinwa
Trevor Halsted
Javier Yu
Mac Schwager
251
33
0
26 Jan 2023
CEDAS: A Compressed Decentralized Stochastic Gradient Method with Improved Convergence
IEEE Transactions on Automatic Control (TAC), 2023
Kun-Yen Huang
Shin-Yi Pu
319
16
0
14 Jan 2023
Why Batch Normalization Damage Federated Learning on Non-IID Data?
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Yanmeng Wang
Qingjiang Shi
Tsung-Hui Chang
FedML
338
53
0
08 Jan 2023
Beyond spectral gap (extended): The role of the topology in decentralized learning
Thijs Vogels
Aymeric Dieuleveut
Martin Jaggi
214
5
0
05 Jan 2023
Network Utility Maximization with Unknown Utility Functions: A Distributed, Data-Driven Bilevel Optimization Approach
ACM Interational Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 2023
Kaiyi Ji
Lei Ying
230
10
0
04 Jan 2023
Decentralized Gradient Tracking with Local Steps
Optimization Methods and Software (OMS), 2023
Yue Liu
Tao Lin
Anastasia Koloskova
Sebastian U. Stich
273
59
0
03 Jan 2023
Addressing Data Heterogeneity in Decentralized Learning via Topological Pre-processing
Waqwoya Abebe
Ali Jannesari
273
0
0
16 Dec 2022
Straggler-Resilient Differentially-Private Decentralized Learning
Information Theory Workshop (ITW), 2022
Yauhen Yakimenka
Chung-Wei Weng
Hsuan-Yin Lin
E. Rosnes
J. Kliewer
435
8
0
06 Dec 2022
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