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1803.08950
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Asynchronous Gradient-Push
23 March 2018
Mahmoud Assran
Michael G. Rabbat
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Papers citing
"Asynchronous Gradient-Push"
30 / 30 papers shown
ADP-VRSGP: Decentralized Learning with Adaptive Differential Privacy via Variance-Reduced Stochastic Gradient Push
Xiaoming Wu
Teng Liu
Xin Wang
Ming Yang
Jiguo Yu
157
1
0
23 Oct 2025
A Tale of Two Learning Algorithms: Multiple Stream Random Walk and Asynchronous Gossip
Peyman Gholami
H. Seferoglu
243
0
0
14 Apr 2025
Adaptive Weighting Push-SUM for Decentralized Optimization with Statistical Diversity
IEEE Transactions on Control of Network Systems (TCNS), 2024
Yiming Zhou
Yifei Cheng
Linli Xu
Enhong Chen
352
2
0
10 Dec 2024
Boosting Asynchronous Decentralized Learning with Model Fragmentation
The Web Conference (WWW), 2024
Sayan Biswas
Anne-Marie Kermarrec
Alexis Marouani
Rafael Pires
Rishi Sharma
M. Vos
318
6
0
16 Oct 2024
DRACO: Decentralized Asynchronous Federated Learning over Row-Stochastic Wireless Networks
IEEE Open Journal of the Communications Society (OJ-COMSOC), 2024
Eunjeong Jeong
Marios Kountouris
358
1
0
19 Jun 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
Asyn2F: An Asynchronous Federated Learning Framework with Bidirectional Model Aggregation
Tien-Dung Cao
Nguyen T. Vuong
Thai Q. Le
Hoang V.N. Dao
Tram Truong-Huu
FedML
181
2
0
03 Mar 2024
Asynchronous Diffusion Learning with Agent Subsampling and Local Updates
Elsa Rizk
Kun Yuan
Ali H. Sayed
FedML
204
3
0
08 Feb 2024
Asynchronous Distributed Optimization with Delay-free Parameters
Xuyang Wu
Changxin Liu
Sindri Magnússon
Mikael Johansson
166
8
0
11 Dec 2023
Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization
International Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Mathieu Even
Anastasia Koloskova
Laurent Massoulié
FedML
381
17
0
01 Nov 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
Convergence Analysis of Decentralized ASGD
Mauro Dalle Lucca Tosi
Martin Theobald
386
3
0
07 Sep 2023
Adaptive Consensus: A network pruning approach for decentralized optimization
SIAM Journal on Optimization (SIOPT), 2023
S. Shah
A. Berahas
Raghu Bollapragada
199
6
0
06 Sep 2023
Straggler-Resilient Decentralized Learning via Adaptive Asynchronous Updates
ACM Interational Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 2023
Efstathia Soufleri
Gang Yan
Maroun Touma
Jian Li
296
7
0
11 Jun 2023
Stochastic Gradient Descent under Markovian Sampling Schemes
International Conference on Machine Learning (ICML), 2023
Mathieu Even
387
41
0
28 Feb 2023
On the convergence result of the gradient-push algorithm on directed graphs with constant stepsize
Woocheol Choi
Doheon Kim
S. Yun
360
3
0
17 Feb 2023
Resource-Constrained Decentralized Federated Learning via Personalized Event-Triggering
Shahryar Zehtabi
Seyyedali Hosseinalipour
Christopher G. Brinton
FedML
330
7
0
23 Nov 2022
FedAvg with Fine Tuning: Local Updates Lead to Representation Learning
Neural Information Processing Systems (NeurIPS), 2022
Liam Collins
Hamed Hassani
Aryan Mokhtari
Sanjay Shakkottai
FedML
260
129
0
27 May 2022
Push-sum Distributed Dual Averaging for Convex Optimization in Multi-agent Systems with Communication Delays
Cong Wang
Shengyuan Xu
Deming Yuan
Baoyong Zhang
Zhengqiang Zhang
202
18
0
03 Dec 2021
ResIST: Layer-Wise Decomposition of ResNets for Distributed Training
Chen Dun
Cameron R. Wolfe
C. Jermaine
Anastasios Kyrillidis
391
23
0
02 Jul 2021
Asynchronous speedup in decentralized optimization
IEEE Transactions on Automatic Control (IEEE TAC), 2021
Mathieu Even
Aymeric Dieuleveut
Laurent Massoulie
338
6
0
07 Jun 2021
A general framework for decentralized optimization with first-order methods
Proceedings of the IEEE (Proc. IEEE), 2020
Ran Xin
Shi Pu
Angelia Nedić
U. Khan
266
106
0
12 Sep 2020
Push-SAGA: A decentralized stochastic algorithm with variance reduction over directed graphs
Muhammad I. Qureshi
Ran Xin
S. Kar
U. Khan
407
29
0
13 Aug 2020
Advances in Asynchronous Parallel and Distributed Optimization
Proceedings of the IEEE (Proc. IEEE), 2020
By Mahmoud Assran
Arda Aytekin
Hamid Reza Feyzmahdavian
M. Johansson
Michael G. Rabbat
288
97
0
24 Jun 2020
Fully Asynchronous Policy Evaluation in Distributed Reinforcement Learning over Networks
Xingyu Sha
Jiaqi Zhang
Keyou You
Jianchao Tan
Tamer Basar
OffRL
451
26
0
01 Mar 2020
Quantized Decentralized Stochastic Learning over Directed Graphs
International Conference on Machine Learning (ICML), 2020
Hossein Taheri
Aryan Mokhtari
Hamed Hassani
Ramtin Pedarsani
478
5
0
23 Feb 2020
Parallel and distributed asynchronous adaptive stochastic gradient methods
Mathematical Programming Computation (MPC), 2020
Yangyang Xu
Yibo Xu
Yonggui Yan
Colin Sutcher-Shepard
Leopold Grinberg
Jiewei Chen
377
7
0
21 Feb 2020
Revisiting Randomized Gossip Algorithms: General Framework, Convergence Rates and Novel Block and Accelerated Protocols
IEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2019
Nicolas Loizou
Peter Richtárik
319
41
0
20 May 2019
Fully Asynchronous Distributed Optimization with Linear Convergence in Directed Networks
Jiaqi Zhang
Keyou You
275
17
0
24 Jan 2019
Stochastic Gradient Push for Distributed Deep Learning
Mahmoud Assran
Nicolas Loizou
Nicolas Ballas
Michael G. Rabbat
444
392
0
27 Nov 2018
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