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1908.00045
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How Good is SGD with Random Shuffling?
Annual Conference Computational Learning Theory (COLT), 2019
31 July 2019
Itay Safran
Ohad Shamir
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Papers citing
"How Good is SGD with Random Shuffling?"
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Variance Reduction Methods Do Not Need to Compute Full Gradients: Improved Efficiency through Shuffling
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Gleb Molodtsov
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Alexey Rebrikov
Aleksandr Beznosikov
576
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20 Feb 2025
Provably Faster Algorithms for Bilevel Optimization via Without-Replacement Sampling
Neural Information Processing Systems (NeurIPS), 2024
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290
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Yi-Ting Ma
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Loss Gradient Gaussian Width based Generalization and Optimization Guarantees
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Joohwan Ko
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Jacob R. Gardner
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Yanlai Yang
Matt Jones
Michael C. Mozer
Mengye Ren
296
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14 Mar 2024
On the Last-Iterate Convergence of Shuffling Gradient Methods
International Conference on Machine Learning (ICML), 2024
Zijian Liu
Zhengyuan Zhou
558
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12 Mar 2024
Last Iterate Convergence of Incremental Methods and Applications in Continual Learning
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Jelena Diakonikolas
355
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11 Mar 2024
Shuffling Momentum Gradient Algorithm for Convex Optimization
Trang H. Tran
Quoc Tran-Dinh
Lam M. Nguyen
285
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Understanding the Training Speedup from Sampling with Approximate Losses
International Conference on Machine Learning (ICML), 2024
Rudrajit Das
Xi Chen
Bertram Ieong
Parikshit Bansal
Sujay Sanghavi
225
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10 Feb 2024
Central Limit Theorem for Two-Timescale Stochastic Approximation with Markovian Noise: Theory and Applications
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Jie Hu
Vishwaraj Doshi
Do Young Eun
430
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17 Jan 2024
High Probability Guarantees for Random Reshuffling
Hengxu Yu
Xiao Li
343
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20 Nov 2023
Convergence of Sign-based Random Reshuffling Algorithms for Nonconvex Optimization
Zhen Qin
Zhishuai Liu
Pan Xu
440
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24 Oct 2023
Corgi^2: A Hybrid Offline-Online Approach To Storage-Aware Data Shuffling For SGD
Etay Livne
Gal Kaplun
Eran Malach
Shai Shalev-Schwatz
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04 Sep 2023
Mini-Batch Optimization of Contrastive Loss
Jaewoong Cho
Kartik K. Sreenivasan
Keon Lee
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Anna Lee
Jy-yong Sohn
Dimitris Papailiopoulos
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366
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12 Jul 2023
Ordering for Non-Replacement SGD
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Baharan Mirzasoleiman
176
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28 Jun 2023
Empirical Risk Minimization with Shuffled SGD: A Primal-Dual Perspective and Improved Bounds
Xu Cai
Cheuk Yin Lin
Jelena Diakonikolas
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311
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21 Jun 2023
On Convergence of Incremental Gradient for Non-Convex Smooth Functions
International Conference on Machine Learning (ICML), 2023
Anastasia Koloskova
N. Doikov
Sebastian U. Stich
Martin Jaggi
423
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30 May 2023
Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning
International Conference on Learning Representations (ICLR), 2023
Patrik Okanovic
R. Waleffe
Vasilis Mageirakos
Konstantinos E. Nikolakakis
Amin Karbasi
Dionysis Kalogerias
Nezihe Merve Gürel
Theodoros Rekatsinas
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288
27
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28 May 2023
Select without Fear: Almost All Mini-Batch Schedules Generalize Optimally
Konstantinos E. Nikolakakis
Amin Karbasi
Dionysis Kalogerias
380
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03 May 2023
High-dimensional limit of one-pass SGD on least squares
Electronic Communications in Probability (ECP), 2023
Elizabeth Collins-Woodfin
Elliot Paquette
409
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13 Apr 2023
Fast Convergence of Random Reshuffling under Over-Parameterization and the Polyak-Łojasiewicz Condition
Chen Fan
Christos Thrampoulidis
Mark Schmidt
253
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02 Apr 2023
Tighter Lower Bounds for Shuffling SGD: Random Permutations and Beyond
International Conference on Machine Learning (ICML), 2023
Jaeyoung Cha
Jaewook Lee
Chulhee Yun
366
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13 Mar 2023
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David Wu
Chulhee Yun
S. Sra
495
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24 Feb 2023
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Yae Jee Cho
Pranay Sharma
Gauri Joshi
Zheng Xu
Satyen Kale
Tong Zhang
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285
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06 Feb 2023
Efficiency Ordering of Stochastic Gradient Descent
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Jie Hu
Vishwaraj Doshi
Do Young Eun
248
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15 Sep 2022
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Neural Information Processing Systems (NeurIPS), 2022
Lam M. Nguyen
Trang H. Tran
322
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13 Jun 2022
Stochastic Gradient Descent without Full Data Shuffle
The VLDB journal (VLDBJ), 2022
Lijie Xu
Delin Qu
Binhang Yuan
Jiawei Jiang
Cédric Renggli
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Guoliang Li
Ji Liu
Wentao Wu
Jieping Ye
Ce Zhang
163
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12 Jun 2022
Sampling without Replacement Leads to Faster Rates in Finite-Sum Minimax Optimization
Neural Information Processing Systems (NeurIPS), 2022
Aniket Das
Bernhard Schölkopf
Michael Muehlebach
333
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07 Jun 2022
Computing the Variance of Shuffling Stochastic Gradient Algorithms via Power Spectral Density Analysis
Carles Domingo-Enrich
225
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Federated Random Reshuffling with Compression and Variance Reduction
Grigory Malinovsky
Peter Richtárik
FedML
396
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08 May 2022
Risk Bounds of Multi-Pass SGD for Least Squares in the Interpolation Regime
Neural Information Processing Systems (NeurIPS), 2022
Difan Zou
Jingfeng Wu
Vladimir Braverman
Quanquan Gu
Sham Kakade
259
8
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07 Mar 2022
Benign Underfitting of Stochastic Gradient Descent
Neural Information Processing Systems (NeurIPS), 2022
Tomer Koren
Roi Livni
Yishay Mansour
Uri Sherman
MLT
414
23
0
27 Feb 2022
Nesterov Accelerated Shuffling Gradient Method for Convex Optimization
International Conference on Machine Learning (ICML), 2022
Trang H. Tran
K. Scheinberg
Lam M. Nguyen
419
16
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07 Feb 2022
Characterizing & Finding Good Data Orderings for Fast Convergence of Sequential Gradient Methods
Amirkeivan Mohtashami
Sebastian U. Stich
Martin Jaggi
324
14
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03 Feb 2022
A Field Guide to Federated Optimization
Jianyu Wang
Zachary B. Charles
Zheng Xu
Gauri Joshi
H. B. McMahan
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Mi Zhang
Tong Zhang
Chunxiang Zheng
Chen Zhu
Wennan Zhu
FedML
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472
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Optimal Rates for Random Order Online Optimization
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Uri Sherman
Tomer Koren
Yishay Mansour
251
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0
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Zeroth-Order Methods for Convex-Concave Minmax Problems: Applications to Decision-Dependent Risk Minimization
C. Maheshwari
Chih-Yuan Chiu
Eric Mazumdar
S. Shankar Sastry
Lillian J. Ratliff
216
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Random Shuffling Beats SGD Only After Many Epochs on Ill-Conditioned Problems
Neural Information Processing Systems (NeurIPS), 2021
Itay Safran
Ohad Shamir
227
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Fast Distributionally Robust Learning with Variance Reduced Min-Max Optimization
International Conference on Artificial Intelligence and Statistics (AISTATS), 2021
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Tianyi Lin
Eric Mazumdar
Sai Li
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245
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Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders
Xinmeng Huang
Kun Yuan
Xianghui Mao
W. Yin
289
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Random Reshuffling with Variance Reduction: New Analysis and Better Rates
Conference on Uncertainty in Artificial Intelligence (UAI), 2021
Grigory Malinovsky
Alibek Sailanbayev
Peter Richtárik
241
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19 Apr 2021
Can Single-Shuffle SGD be Better than Reshuffling SGD and GD?
Chulhee Yun
S. Sra
Ali Jadbabaie
236
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12 Mar 2021
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