Strong convergence and bounded perturbation resilience of a modified proximal gradient algorithm

doi:10.1186/s13660-018-1695-x

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	Strong convergence and bounded perturbation resilience of a modified proximal gradient algorithm
	Guo,Yanni; Cui,Wei
	2018-05-02
发表期刊	Journal of Inequalities and Applications
ISSN	1029-242X
卷号	2018 期号:1
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.
关键词	Strong convergence Bounded perturbation resilience Modified proximal gradient algorithm Viscosity approximation Convex minimization problem
DOI	10.1186/s13660-018-1695-x
语种	英语
WOS记录号	BMC:10.1186/s13660-018-1695-x
出版者	Springer International Publishing
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/417
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).