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...

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Vydané v:	Computational optimization and applications Ročník 69; číslo 2; s. 297 - 324
Hlavní autori:	Wen, Bo, Chen, Xiaojun, Pong, Ting Kei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.03.2018 Springer Nature B.V
Predmet:	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
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