Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data

Stochastic variance reduced methods have gained a lot of interest recently for empirical risk minimization due to its appealing run time complexity. When the data size is large and disjointly stored on different machines, it becomes imperative to distribute the implementation of such variance reduce...

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Bibliographic Details

Published in:	arXiv.org
Main Authors:	Cen, Shicong, Zhang, Huishuai, Chi, Yuejie, Chen, Wei, Tie-Yan, Liu
Format:	Paper
Language:	English
Published:	Ithaca Cornell University Library, arXiv.org 09.07.2020
Subjects:	Algorithms Convergence Empirical analysis Regularization Sampling methods Smoothness
ISSN:	2331-8422
Online Access:	Get full text
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