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Improved Analysis and Rates for Variance Reduction under
  Without-replacement Sampling Orders

Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders

25 April 2021
Xinmeng Huang
Kun Yuan
Xianghui Mao
W. Yin
ArXivPDFHTML

Papers citing "Improved Analysis and Rates for Variance Reduction under Without-replacement Sampling Orders"

5 / 5 papers shown
Title
Variance Reduction Methods Do Not Need to Compute Full Gradients: Improved Efficiency through Shuffling
Variance Reduction Methods Do Not Need to Compute Full Gradients: Improved Efficiency through Shuffling
Daniil Medyakov
Gleb Molodtsov
S. Chezhegov
Alexey Rebrikov
Aleksandr Beznosikov
103
0
0
21 Feb 2025
High Probability Guarantees for Random Reshuffling
High Probability Guarantees for Random Reshuffling
Hengxu Yu
Xiao Li
42
2
0
20 Nov 2023
Random-reshuffled SARAH does not need a full gradient computations
Random-reshuffled SARAH does not need a full gradient computations
Aleksandr Beznosikov
Martin Takáč
26
7
0
26 Nov 2021
Surpassing Gradient Descent Provably: A Cyclic Incremental Method with
  Linear Convergence Rate
Surpassing Gradient Descent Provably: A Cyclic Incremental Method with Linear Convergence Rate
Aryan Mokhtari
Mert Gurbuzbalaban
Alejandro Ribeiro
27
36
0
01 Nov 2016
Incremental Majorization-Minimization Optimization with Application to
  Large-Scale Machine Learning
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning
Julien Mairal
79
317
0
18 Feb 2014
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