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

The 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...

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Vydané v:	Journal of inequalities and applications Ročník 2018; číslo 1; s. 103 - 15
Hlavní autori:	Guo, Yanni, Cui, Wei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Cham Springer International Publishing 2018 Springer Nature B.V SpringerOpen
Predmet:	Algorithms Analysis Applications of Mathematics Bounded perturbation resilience Convergence Convex minimization problem Hilbert space Mathematics Mathematics and Statistics Modified proximal gradient algorithm Optimization Perturbation Resilience Strong convergence Viscosity approximation Modified proximal gradient algorithm Strong convergence Bounded perturbation resilience Convex minimization problem Viscosity approximation
ISSN:	1029-242X, 1025-5834, 1029-242X
On-line prístup:	Získať plný text
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