Communities
Connect sessions
AI calendar
Organizations
Join Slack
Contact Sales
Search
Open menu
Home
Papers
1606.04809
Cited By
v1
v2
v3 (latest)
ASAGA: Asynchronous Parallel SAGA
15 June 2016
Rémi Leblond
Fabian Pedregosa
Damien Scieur
AI4TS
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"ASAGA: Asynchronous Parallel SAGA"
50 / 58 papers shown
Asynchronous Decentralized SGD under Non-Convexity: A Block-Coordinate Descent Framework
Yijie Zhou
Shi Pu
208
2
0
15 May 2025
Distributed Stochastic Gradient Descent with Staleness: A Stochastic Delay Differential Equation Based Framework
Siyuan Yu
Wei Chen
H. V. Poor
416
0
0
17 Jun 2024
Distributed Adaptive Greedy Quasi-Newton Methods with Explicit Non-asymptotic Convergence Bounds
Yubo Du
Keyou You
275
7
0
30 Nov 2023
Scaling up Stochastic Gradient Descent for Non-convex Optimisation
Machine-mediated learning (ML), 2022
S. Mohamad
H. Alamri
A. Bouchachia
250
3
0
06 Oct 2022
Distributed Dynamic Safe Screening Algorithms for Sparse Regularization
Runxue Bao
Xidong Wu
Wenhan Xian
Heng-Chiao Huang
252
1
0
23 Apr 2022
Finite-Time Consensus Learning for Decentralized Optimization with Nonlinear Gossiping
Junya Chen
Sijia Wang
Lawrence Carin
Chenyang Tao
171
3
0
04 Nov 2021
Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization
Kaiwen Zhou
Anthony Man-Cho So
James Cheng
285
1
0
30 Sep 2021
Asynchronous Iterations in Optimization: New Sequence Results and Sharper Algorithmic Guarantees
Journal of machine learning research (JMLR), 2021
Hamid Reza Feyzmahdavian
M. Johansson
261
29
0
09 Sep 2021
L-DQN: An Asynchronous Limited-Memory Distributed Quasi-Newton Method
Bugra Can
Saeed Soori
M. Dehnavi
Mert Gurbuzbalaban
333
2
0
20 Aug 2021
Federated Learning with Buffered Asynchronous Aggregation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
John Nguyen
Kshitiz Malik
Hongyuan Zhan
Ashkan Yousefpour
Michael G. Rabbat
Mani Malek
Dzmitry Huba
FedML
445
425
0
11 Jun 2021
Decoupled Greedy Learning of CNNs for Synchronous and Asynchronous Distributed Learning
Eugene Belilovsky
Louis Leconte
Lucas Caccia
Michael Eickenberg
Edouard Oyallon
236
9
0
11 Jun 2021
Pufferfish: Communication-efficient Models At No Extra Cost
Conference on Machine Learning and Systems (MLSys), 2021
Hongyi Wang
Saurabh Agarwal
Dimitris Papailiopoulos
183
74
0
05 Mar 2021
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices
Neural Information Processing Systems (NeurIPS), 2021
Max Ryabinin
Eduard A. Gorbunov
Vsevolod Plokhotnyuk
Gennady Pekhimenko
448
49
0
04 Mar 2021
Secure Bilevel Asynchronous Vertical Federated Learning with Backward Updating
AAAI Conference on Artificial Intelligence (AAAI), 2021
Qingsong Zhang
Bin Gu
Cheng Deng
Heng-Chiao Huang
FedML
143
80
0
01 Mar 2021
Sum-Rate-Distortion Function for Indirect Multiterminal Source Coding in Federated Learning
International Symposium on Information Theory (ISIT), 2021
Naifu Zhang
M. Tao
Jia Wang
FedML
325
5
0
21 Jan 2021
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism
Journal of machine learning research (JMLR), 2020
Yu-Guan Hsieh
F. Iutzeler
J. Malick
P. Mertikopoulos
AI4CE
375
36
0
21 Dec 2020
Asynchrony and Acceleration in Gossip Algorithms
Mathieu Even
Aymeric Dieuleveut
Laurent Massoulié
324
8
0
04 Nov 2020
Variance-Reduced Methods for Machine Learning
Proceedings of the IEEE (Proc. IEEE), 2020
Robert Mansel Gower
Mark Schmidt
Francis R. Bach
Peter Richtárik
330
153
0
02 Oct 2020
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters
Filip Hanzely
232
0
0
26 Aug 2020
Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning
Bin Gu
An Xu
Zhouyuan Huo
Cheng Deng
Heng-Chiao Huang
FedML
347
31
0
14 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
Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization
Chaobing Song
Yong Jiang
Yi-An Ma
524
25
0
18 Jun 2020
An Optimal Algorithm for Decentralized Finite Sum Optimization
Aymeric Dieuleveut
Francis R. Bach
Laurent Massoulie
267
49
0
20 May 2020
On the Convergence Analysis of Asynchronous SGD for Solving Consistent Linear Systems
Linear Algebra and its Applications (LAA), 2020
Atal Narayan Sahu
Aritra Dutta
Aashutosh Tiwari
Peter Richtárik
302
8
0
05 Apr 2020
Elastic Consistency: A General Consistency Model for Distributed Stochastic Gradient Descent
Giorgi Nadiradze
Ilia Markov
Bapi Chatterjee
Vyacheslav Kungurtsev
Dan Alistarh
FedML
302
14
0
16 Jan 2020
ASYNC: A Cloud Engine with Asynchrony and History for Distributed Machine Learning
IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2019
Saeed Soori
Bugra Can
Mert Gurbuzbalaban
M. Dehnavi
GNN
OffRL
391
4
0
19 Jul 2019
A Unifying Framework for Variance Reduction Algorithms for Finding Zeroes of Monotone Operators
Xun Zhang
W. Haskell
Z. Ye
215
3
0
22 Jun 2019
Scaling Up Quasi-Newton Algorithms: Communication Efficient Distributed SR1
International Conference on Machine Learning, Optimization, and Data Science (MOD), 2019
Majid Jahani
M. Nazari
S. Rusakov
A. Berahas
Martin Takávc
352
17
0
30 May 2019
An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums
Neural Information Processing Systems (NeurIPS), 2019
Aymeric Dieuleveut
Francis R. Bach
Laurent Massoulie
237
33
0
27 May 2019
Block stochastic gradient descent for large-scale tomographic reconstruction in a parallel network
Yushan Gao
A. Biguri
T. Blumensath
241
3
0
28 Mar 2019
Asynchronous Delay-Aware Accelerated Proximal Coordinate Descent for Nonconvex Nonsmooth Problems
Ehsan Kazemi
Liqiang Wang
161
2
0
05 Feb 2019
Asynchronous Accelerated Proximal Stochastic Gradient for Strongly Convex Distributed Finite Sums
Aymeric Dieuleveut
Francis R. Bach
Laurent Massoulié
FedML
297
26
0
28 Jan 2019
Decoupled Greedy Learning of CNNs
Eugene Belilovsky
Michael Eickenberg
Edouard Oyallon
454
131
0
23 Jan 2019
Distributed Learning with Sparse Communications by Identification
Dmitry Grishchenko
F. Iutzeler
J. Malick
Massih-Reza Amini
242
19
0
10 Dec 2018
Asynchronous Stochastic Composition Optimization with Variance Reduction
Shuheng Shen
Linli Xu
Jingchang Liu
Junliang Guo
Qing Ling
181
2
0
15 Nov 2018
Distributed Learning over Unreliable Networks
Chen Yu
Hanlin Tang
Cédric Renggli
S. Kassing
Ankit Singla
Dan Alistarh
Ce Zhang
Ji Liu
OOD
344
65
0
17 Oct 2018
POLO: a POLicy-based Optimization library
Arda Aytekin
Martin Biel
M. Johansson
165
3
0
08 Oct 2018
Anytime Stochastic Gradient Descent: A Time to Hear from all the Workers
Nuwan S. Ferdinand
S. Draper
273
20
0
06 Oct 2018
Sparsified SGD with Memory
Sebastian U. Stich
Jean-Baptiste Cordonnier
Martin Jaggi
473
858
0
20 Sep 2018
Fast Variance Reduction Method with Stochastic Batch Size
Xuanqing Liu
Cho-Jui Hsieh
396
6
0
07 Aug 2018
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates
International Conference on Machine Learning (ICML), 2018
Kaiwen Zhou
Fanhua Shang
James Cheng
238
82
0
28 Jun 2018
ATOMO: Communication-efficient Learning via Atomic Sparsification
Hongyi Wang
Scott Sievert
Zachary B. Charles
Shengchao Liu
S. Wright
Dimitris Papailiopoulos
426
382
0
11 Jun 2018
Federated Learning with Non-IID Data
Yue Zhao
Meng Li
Liangzhen Lai
Naveen Suda
Damon Civin
Vikas Chandra
FedML
798
3,173
0
02 Jun 2018
Double Quantization for Communication-Efficient Distributed Optimization
Yue Yu
Jiaxiang Wu
Longbo Huang
MQ
462
59
0
25 May 2018
Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization
G. Scutari
Ying Sun
422
77
0
17 May 2018
Proximal SCOPE for Distributed Sparse Learning: Better Data Partition Implies Faster Convergence Rate
Neural Information Processing Systems (NeurIPS), 2018
Shen-Yi Zhao
Gong-Duo Zhang
Ming-Wei Li
Wu-Jun Li
223
8
0
15 Mar 2018
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD
Sanghamitra Dutta
Gauri Joshi
Soumyadip Ghosh
Parijat Dube
P. Nagpurkar
521
203
0
03 Mar 2018
Improved asynchronous parallel optimization analysis for stochastic incremental methods
Rémi Leblond
Fabian Pedregosa
Damien Scieur
402
75
0
11 Jan 2018
AdaBatch: Efficient Gradient Aggregation Rules for Sequential and Parallel Stochastic Gradient Methods
Alexandre Défossez
Francis R. Bach
ODL
112
17
0
06 Nov 2017
Smooth and Sparse Optimal Transport
Mathieu Blondel
Vivien Seguy
Antoine Rolet
OT
332
198
0
17 Oct 2017
1
2
Next
Page 1 of 2
