中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Strong convergence and bounded perturbation resilience of a modified proximal gradient algorithm

文献类型:期刊论文

作者Guo,Yanni; Cui,Wei
刊名Journal of Inequalities and Applications
出版日期2018-05-02
卷号2018期号:1
关键词Strong convergence Bounded perturbation resilience Modified proximal gradient algorithm Viscosity approximation Convex minimization problem
ISSN号1029-242X
DOI10.1186/s13660-018-1695-x
英文摘要AbstractThe proximal gradient algorithm is an appealing approach in finding solutions of non-smooth composite optimization problems, which may only has weak convergence in the infinite-dimensional setting. In this paper, we introduce a modified proximal gradient algorithm with outer perturbations in Hilbert space and prove that the algorithm converges strongly to a solution of the composite optimization problem. We also discuss the bounded perturbation resilience of the basic algorithm of this iterative scheme and illustrate it with an application.
语种英语
WOS记录号BMC:10.1186/S13660-018-1695-X
出版者Springer International Publishing
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/416]  
专题中国科学院数学与系统科学研究院
通讯作者Guo,Yanni
作者单位
推荐引用方式
GB/T 7714
Guo,Yanni,Cui,Wei. Strong convergence and bounded perturbation resilience of a modified proximal gradient algorithm[J]. Journal of Inequalities and Applications,2018,2018(1).
APA Guo,Yanni,&Cui,Wei.(2018).Strong convergence and bounded perturbation resilience of a modified proximal gradient algorithm.Journal of Inequalities and Applications,2018(1).
MLA Guo,Yanni,et al."Strong convergence and bounded perturbation resilience of a modified proximal gradient algorithm".Journal of Inequalities and Applications 2018.1(2018).

入库方式: OAI收割

来源:数学与系统科学研究院

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