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1702.06269
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Memory and Communication Efficient Distributed Stochastic Optimization with Minibatch-Prox
Annual Conference Computational Learning Theory (COLT), 2017
21 February 2017
Jialei Wang
Weiran Wang
Nathan Srebro
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Papers citing
"Memory and Communication Efficient Distributed Stochastic Optimization with Minibatch-Prox"
33 / 33 papers shown
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Sharper Analysis for Minibatch Stochastic Proximal Point Methods: Stability, Smoothness, and Deviation
Journal of machine learning research (JMLR), 2023
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Uniform Stability for First-Order Empirical Risk Minimization
Annual Conference Computational Learning Theory (COLT), 2022
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Tomer Koren
154
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On Convergence of FedProx: Local Dissimilarity Invariant Bounds, Non-smoothness and Beyond
Neural Information Processing Systems (NeurIPS), 2022
Xiao-Tong Yuan
P. Li
FedML
194
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10 Jun 2022
Minibatch and Momentum Model-based Methods for Stochastic Weakly Convex Optimization
Neural Information Processing Systems (NeurIPS), 2021
Qi Deng
Wenzhi Gao
218
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06 Jun 2021
Algorithmic Instabilities of Accelerated Gradient Descent
Neural Information Processing Systems (NeurIPS), 2021
Amit Attia
Tomer Koren
145
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03 Feb 2021
The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication
Annual Conference Computational Learning Theory (COLT), 2021
Blake E. Woodworth
Brian Bullins
Ohad Shamir
Nathan Srebro
260
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02 Feb 2021
Inverse Multiobjective Optimization Through Online Learning
Chaosheng Dong
Yijia Wang
Bo Zeng
131
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12 Oct 2020
Adaptive Periodic Averaging: A Practical Approach to Reducing Communication in Distributed Learning
Peng Jiang
G. Agrawal
137
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Stochastic Proximal Gradient Algorithm with Minibatches. Application to Large Scale Learning Models
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C. Paduraru
Paul Irofti
115
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30 Mar 2020
Is Local SGD Better than Minibatch SGD?
International Conference on Machine Learning (ICML), 2020
Blake E. Woodworth
Kumar Kshitij Patel
Sebastian U. Stich
Zhen Dai
Brian Bullins
H. B. McMahan
Ohad Shamir
Nathan Srebro
FedML
299
271
0
18 Feb 2020
Parallel Restarted SPIDER -- Communication Efficient Distributed Nonconvex Optimization with Optimal Computation Complexity
Pranay Sharma
Swatantra Kafle
Prashant Khanduri
Saikiran Bulusu
K. Rajawat
P. Varshney
FedML
285
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0
12 Dec 2019
Least Squares Approximation for a Distributed System
Journal of Computational And Graphical Statistics (JCGS), 2019
Xuening Zhu
Feng Li
Hansheng Wang
394
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14 Aug 2019
On Convergence of Distributed Approximate Newton Methods: Globalization, Sharper Bounds and Beyond
Journal of machine learning research (JMLR), 2019
Xiao-Tong Yuan
Ping Li
248
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06 Aug 2019
Communication-Efficient Accurate Statistical Estimation
Jianqing Fan
Yongyi Guo
Kaizheng Wang
175
134
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12 Jun 2019
Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data
IEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2019
Shicong Cen
Huishuai Zhang
Yuejie Chi
Wei-neng Chen
Tie-Yan Liu
FedML
225
29
0
29 May 2019
A Distributed Hierarchical SGD Algorithm with Sparse Global Reduction
Fan Zhou
Guojing Cong
157
8
0
12 Mar 2019
Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the
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Convergence Rate
Lijun Zhang
Zhi Zhou
179
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27 Jan 2019
ASVRG: Accelerated Proximal SVRG
Fanhua Shang
L. Jiao
Kaiwen Zhou
James Cheng
Yan Ren
Yufei Jin
ODL
277
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07 Oct 2018
Generalized Inverse Optimization through Online Learning
Chaosheng Dong
Yiran Chen
Bo Zeng
238
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0
03 Oct 2018
Don't Use Large Mini-Batches, Use Local SGD
Tao Lin
Sebastian U. Stich
Kumar Kshitij Patel
Martin Jaggi
718
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22 Aug 2018
COLA: Decentralized Linear Learning
Lie He
An Bian
Martin Jaggi
244
130
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13 Aug 2018
Robust Implicit Backpropagation
Francois Fagan
G. Iyengar
137
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The Effect of Network Width on the Performance of Large-batch Training
Lingjiao Chen
Hongyi Wang
Jinman Zhao
Dimitris Papailiopoulos
Paraschos Koutris
195
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11 Jun 2018
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization
Blake E. Woodworth
Jialei Wang
Adam D. Smith
H. B. McMahan
Nathan Srebro
245
126
0
25 May 2018
Double Quantization for Communication-Efficient Distributed Optimization
Yue Yu
Jiaxiang Wu
Longbo Huang
MQ
342
59
0
25 May 2018
Distributed Stochastic Optimization via Adaptive SGD
Ashok Cutkosky
R. Busa-Fekete
FedML
187
24
0
16 Feb 2018
Distributed Stochastic Multi-Task Learning with Graph Regularization
Weiran Wang
Jialei Wang
Mladen Kolar
Nathan Srebro
FedML
114
21
0
11 Feb 2018
Gradient Sparsification for Communication-Efficient Distributed Optimization
Neural Information Processing Systems (NeurIPS), 2017
Jianqiao Wangni
Jialei Wang
Ji Liu
Tong Zhang
282
572
0
26 Oct 2017
Stochastic Nonconvex Optimization with Large Minibatches
Weiran Wang
Nathan Srebro
369
27
0
25 Sep 2017
On the convergence properties of a
K
K
K
-step averaging stochastic gradient descent algorithm for nonconvex optimization
Fan Zhou
Guojing Cong
383
243
0
03 Aug 2017
Improved Optimization of Finite Sums with Minibatch Stochastic Variance Reduced Proximal Iterations
Jialei Wang
Tong Zhang
251
12
0
21 Jun 2017
Gradient Diversity: a Key Ingredient for Scalable Distributed Learning
Dong Yin
A. Pananjady
Max Lam
Dimitris Papailiopoulos
Kannan Ramchandran
Peter L. Bartlett
210
12
0
18 Jun 2017
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