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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Veröffentlicht in:	arXiv.org
Hauptverfasser:	Cen, Shicong, Zhang, Huishuai, Chi, Yuejie, Chen, Wei, Tie-Yan, Liu
Format:	Paper
Sprache:	Englisch
Veröffentlicht:	Ithaca Cornell University Library, arXiv.org 09.07.2020
Schlagworte:	Algorithms Convergence Empirical analysis Regularization Sampling methods Smoothness
ISSN:	2331-8422
Online-Zugang:	Volltext
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