New inertial proximal gradient methods for unconstrained convex optimization problems

The proximal gradient method is a highly powerful tool for solving the composite convex optimization problem. In this paper, firstly, we propose inexact inertial acceleration methods based on the viscosity approximation and proximal scaled gradient algorithm to accelerate the convergence of the algo...

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Bibliographic Details
Published in:	Journal of inequalities and applications Vol. 2020; no. 1; pp. 1 - 18
Main Authors:	Duan, Peichao, Zhang, Yiqun, Bu, Qinxiong
Format:	Journal Article
Language:	English
Published:	Cham Springer International Publishing 07.12.2020 Springer Nature B.V SpringerOpen
Subjects:	Algorithms Alternated inertial acceleration Analysis Applications of Mathematics Computational geometry Convergence Convex analysis Convex optimization Convexity Inertial acceleration Mathematics Mathematics and Statistics Optimization Proximal operator Viscosity approximation 47H10 Alternated inertial acceleration Inertial acceleration Convex optimization 90C25 47H09 65K10 Proximal operator 47J25 Viscosity approximation
ISSN:	1029-242X, 1025-5834, 1029-242X
Online Access:	Get full text
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