On Globally Q-Linear Convergence of a Splitting Method for Group Lasso

被引：0

作者：

Dong Y.-D. ^{[1
]}

Zhang H.-B. ^{[2
]}

Gao H. ^{[2
,3
]}

机构：

[1] School of Mathematics and Statistics, Zhengzhou University, Zhengzhou

[2] College of Applied Sciences, Beijing University of Technology, Beijing

[3] College of Mathematics and Computational Science, Hunan First Normal University, Changsha

来源：

Journal of the Operations Research Society of China | 2018年 / 6卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Group Lasso; Proximal gradient method; Q-linear rate of convergence; Splitting method;

D O I：

10.1007/s40305-017-0176-0

中图分类号：

学科分类号：

摘要：

In this paper, we discuss a splitting method for group Lasso. By assuming that the sequence of the step lengths has positive lower bound and positive upper bound (unrelated to the given problem data), we prove its Q-linear rate of convergence of the distance sequence of the iterates to the solution set. Moreover, we make comparisons with convergence of the proximal gradient method analyzed very recently. © 2017, Operations Research Society of China, Periodicals Agency of Shanghai University, Science Press, and Springer-Verlag GmbH Germany.

引用

页码：445 / 454

页数：9

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