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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
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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
Second-Order Guarantees in Centralized, Federated and Decentralized Nonconvex Optimization
Communications in Information and Systems (CIS), 2020
Stefan Vlaski
Ali H. Sayed
201
5
0
31 Mar 2020
A Hybrid-Order Distributed SGD Method for Non-Convex Optimization to Balance Communication Overhead, Computational Complexity, and Convergence Rate
Naeimeh Omidvar
M. Maddah-ali
Hamed Mahdavi
ODL
95
3
0
27 Mar 2020
A Unified Theory of Decentralized SGD with Changing Topology and Local Updates
International Conference on Machine Learning (ICML), 2020
Anastasia Koloskova
Nicolas Loizou
Sadra Boreiri
Martin Jaggi
Sebastian U. Stich
FedML
539
593
0
23 Mar 2020
Communication-Efficient Distributed Deep Learning: A Comprehensive Survey
Zhenheng Tang
Shaoshuai Shi
Wei Wang
Yue Liu
Xiaowen Chu
240
54
0
10 Mar 2020
Decentralized SGD with Over-the-Air Computation
Global Communications Conference (GLOBECOM), 2020
Emre Ozfatura
Stefano Rini
Deniz Gunduz
169
40
0
06 Mar 2020
Communication optimization strategies for distributed deep neural network training: A survey
Shuo Ouyang
Dezun Dong
Yemao Xu
Liquan Xiao
327
12
0
06 Mar 2020
Buffered Asynchronous SGD for Byzantine Learning
Journal of machine learning research (JMLR), 2020
Yi-Rui Yang
Wu-Jun Li
FedML
235
5
0
02 Mar 2020
Scalable Learning Paradigms for Data-Driven Wireless Communication
IEEE Communications Magazine (IEEE Commun. Mag.), 2020
Yue Xu
Feng Yin
Wenjun Xu
Chia-han Lee
Jiaru Lin
Shuguang Cui
156
27
0
01 Mar 2020
Fully Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks
Xingyu Sha
Jiaqi Zhang
Keyou You
Jianchao Tan
Tamer Basar
OffRL
350
26
0
01 Mar 2020
Decentralized gradient methods: does topology matter?
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020
Giovanni Neglia
Chuan Xu
Don Towsley
G. Calbi
141
60
0
28 Feb 2020
Moniqua: Modulo Quantized Communication in Decentralized SGD
International Conference on Machine Learning (ICML), 2020
Yucheng Lu
Christopher De Sa
MQ
207
52
0
26 Feb 2020
Network-Density-Controlled Decentralized Parallel Stochastic Gradient Descent in Wireless Systems
Koya Sato
Yasuyuki Satoh
D. Sugimura
92
2
0
25 Feb 2020
Distributed Training of Deep Neural Network Acoustic Models for Automatic Speech Recognition
IEEE Signal Processing Magazine (IEEE Signal Process. Mag.), 2020
Xiaodong Cui
Wei Zhang
Ulrich Finkler
G. Saon
M. Picheny
David S. Kung
121
19
0
24 Feb 2020
Quantized Decentralized Stochastic Learning over Directed Graphs
International Conference on Machine Learning (ICML), 2020
Hossein Taheri
Aryan Mokhtari
Hamed Hassani
Ramtin Pedarsani
371
5
0
23 Feb 2020
Communication-Efficient Decentralized Learning with Sparsification and Adaptive Peer Selection
IEEE International Conference on Distributed Computing Systems (ICDCS), 2020
Zhenheng Tang
Shaoshuai Shi
Xiaowen Chu
FedML
154
68
0
22 Feb 2020
Bounding the expected run-time of nonconvex optimization with early stopping
Conference on Uncertainty in Artificial Intelligence (UAI), 2020
Thomas Flynn
K. Yu
A. Malik
Nicolas DÍmperio
Shinjae Yoo
227
2
0
20 Feb 2020
Byzantine-resilient Decentralized Stochastic Gradient Descent
Shangwei Guo
Tianwei Zhang
Hanzhou Yu
Xiaofei Xie
Lei Ma
Tao Xiang
Yang Liu
223
64
0
20 Feb 2020
Gradient tracking and variance reduction for decentralized optimization and machine learning
Ran Xin
S. Kar
U. Khan
160
10
0
13 Feb 2020
Turbo-Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning
IEEE Journal on Selected Areas in Information Theory (JSAIT), 2020
Jinhyun So
Başak Güler
A. Avestimehr
FedML
336
349
0
11 Feb 2020
MDLdroid: a ChainSGD-reduce Approach to Mobile Deep Learning for Personal Mobile Sensing
International Symposium on Information Processing in Sensor Networks (IPSN), 2020
Yu Zhang
Tao Gu
Xi Zhang
FedML
161
25
0
07 Feb 2020
Improving Efficiency in Large-Scale Decentralized Distributed Training
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020
Wei Zhang
Xiaodong Cui
Abdullah Kayi
Mingrui Liu
Ulrich Finkler
...
Youssef Mroueh
A. Buyuktosunoglu
Payel Das
David S. Kung
M. Picheny
142
16
0
04 Feb 2020
Elastic Consistency: A General Consistency Model for Distributed Stochastic Gradient Descent
Giorgi Nadiradze
Ilia Markov
Bapi Chatterjee
Vyacheslav Kungurtsev
Dan Alistarh
FedML
247
14
0
16 Jan 2020
Distributed Learning in the Non-Convex World: From Batch to Streaming Data, and Beyond
Tsung-Hui Chang
Mingyi Hong
Hoi-To Wai
Xinwei Zhang
Songtao Lu
GNN
190
13
0
14 Jan 2020
Private and Communication-Efficient Edge Learning: A Sparse Differential Gaussian-Masking Distributed SGD Approach
ACM Interational Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 2020
Xin Zhang
Minghong Fang
Jia-Wei Liu
Zhengyuan Zhu
FedML
266
30
0
12 Jan 2020
PIRATE: A Blockchain-based Secure Framework of Distributed Machine Learning in 5G Networks
Sicong Zhou
Huawei Huang
Wuhui Chen
Zibin Zheng
Song Guo
FedML
134
81
0
17 Dec 2019
Advances and Open Problems in Federated Learning
Peter Kairouz
H. B. McMahan
Brendan Avent
A. Bellet
M. Bennis
...
Zheng Xu
Qiang Yang
Felix X. Yu
Han Yu
Sen Zhao
FedML
AI4CE
662
7,599
0
10 Dec 2019
Learn Electronic Health Records by Fully Decentralized Federated Learning
Songtao Lu
Yawen Zhang
Yunlong Wang
C. Mack
FedML
124
26
0
04 Dec 2019
D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems
AAAI Conference on Artificial Intelligence (AAAI), 2019
Taoxing Pan
Jun Liu
Jie Wang
97
18
0
28 Nov 2019
Local AdaAlter: Communication-Efficient Stochastic Gradient Descent with Adaptive Learning Rates
Cong Xie
Oluwasanmi Koyejo
Indranil Gupta
Yanghua Peng
259
45
0
20 Nov 2019
Federated Learning with Differential Privacy: Algorithms and Performance Analysis
IEEE Transactions on Information Forensics and Security (IEEE TIFS), 2019
Kang Wei
Jun Li
Ming Ding
Chuan Ma
Heng Yang
Farokhi Farhad
Shi Jin
Tony Q.S. Quek
H. Vincent Poor
FedML
541
1,995
0
01 Nov 2019
On the Convergence of Local Descent Methods in Federated Learning
Farzin Haddadpour
M. Mahdavi
FedML
265
305
0
31 Oct 2019
SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Stochastic Optimization
Navjot Singh
Deepesh Data
Jemin George
Suhas Diggavi
169
24
0
31 Oct 2019
Linear Speedup in Saddle-Point Escape for Decentralized Non-Convex Optimization
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019
Stefan Vlaski
Ali H. Sayed
190
2
0
30 Oct 2019
A Decentralized Parallel Algorithm for Training Generative Adversarial Nets
Mingrui Liu
Wei Zhang
Youssef Mroueh
Xiaodong Cui
Jerret Ross
Tianbao Yang
Payel Das
317
78
0
28 Oct 2019
Asynchronous Decentralized SGD with Quantized and Local Updates
Neural Information Processing Systems (NeurIPS), 2019
Giorgi Nadiradze
Amirmojtaba Sabour
Peter Davies
Shigang Li
Dan Alistarh
275
52
0
27 Oct 2019
The Scalability for Parallel Machine Learning Training Algorithm: Dataset Matters
Daning Cheng
Hanping Zhang
Fen Xia
Shigang Li
Yunquan Zhang
165
1
0
25 Oct 2019
Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
Jinming Xu
Ye Tian
Ying Sun
G. Scutari
356
39
0
23 Oct 2019
Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning
IEEE Transactions on Communications (IEEE Trans. Commun.), 2019
Anis Elgabli
Jihong Park
Amrit Singh Bedi
Chaouki Ben Issaid
M. Bennis
Vaneet Aggarwal
533
72
0
23 Oct 2019
Communication-Efficient Local Decentralized SGD Methods
Xiang Li
Wenhao Yang
Shusen Wang
Zhihua Zhang
273
54
0
21 Oct 2019
Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks
Neural Information Processing Systems (NeurIPS), 2019
Jy-yong Sohn
Dong-Jun Han
Beongjun Choi
Jaekyun Moon
FedML
288
40
0
14 Oct 2019
Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: A Joint Gradient Estimation and Tracking Approach
International Conference on Machine Learning (ICML), 2019
Haoran Sun
Songtao Lu
Mingyi Hong
219
33
0
13 Oct 2019
General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme
Neural Information Processing Systems (NeurIPS), 2019
Tao Sun
Yuejiao Sun
Dongsheng Li
Qing Liao
111
18
0
11 Oct 2019
Central Server Free Federated Learning over Single-sided Trust Social Networks
Chaoyang He
Conghui Tan
Hanlin Tang
Delin Qu
Ji Liu
FedML
253
80
0
11 Oct 2019
Straggler-Agnostic and Communication-Efficient Distributed Primal-Dual Algorithm for High-Dimensional Data Mining
Zhouyuan Huo
Heng-Chiao Huang
FedML
132
5
0
09 Oct 2019
Variance-Reduced Decentralized Stochastic Optimization with Gradient Tracking -- Part II: GT-SVRG
Ran Xin
U. Khan
S. Kar
304
8
0
08 Oct 2019
SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum
International Conference on Learning Representations (ICLR), 2019
Jianyu Wang
Vinayak Tantia
Nicolas Ballas
Michael G. Rabbat
349
216
0
01 Oct 2019
Matrix Sketching for Secure Collaborative Machine Learning
International Conference on Machine Learning (ICML), 2019
Mengjiao Zhang
Shusen Wang
FedML
313
16
0
24 Sep 2019
Decentralized Markov Chain Gradient Descent
Tao Sun
Dongsheng Li
BDL
194
12
0
23 Sep 2019
Heterogeneity-Aware Asynchronous Decentralized Training
Qinyi Luo
Jiaao He
Youwei Zhuo
Xuehai Qian
137
8
0
17 Sep 2019
Communication-Efficient Distributed Learning via Lazily Aggregated Quantized Gradients
Neural Information Processing Systems (NeurIPS), 2019
Jun Sun
Tianyi Chen
G. Giannakis
Zaiyue Yang
180
99
0
17 Sep 2019
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