A proximal difference-of-convex algorithm with extrapolation

We consider a class of difference-of-convex (DC) optimization problems whose objective is level-bounded and is the sum of a smooth convex function with Lipschitz gradient, a proper closed convex function and a continuous concave function. While this kind of problems can be solved by the classical di...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Computational optimization and applications Jg. 69; H. 2; S. 297 - 324
Hauptverfasser:	Wen, Bo, Chen, Xiaojun, Pong, Ting Kei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.03.2018 Springer Nature B.V
Schlagworte:	Algorithms Continuity (mathematics) Convergence Convex and Discrete Geometry Decomposition Economic models Extrapolation Formulations Iterative methods Management Science Mathematical models Mathematics Mathematics and Statistics Operations Research Operations Research/Decision Theory Optimization Shrinkage Statistics Nonsmooth Extrapolation Kurdyka-Łojasiewicz inequality 90C30 65K05 90C26 Difference-of-convex problems Nonconvex
ISSN:	0926-6003, 1573-2894
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!