New Bregman proximal type algorithms for solving DC optimization problems

Difference of Convex (DC) optimization problems have objective functions that are differences between two convex functions. Representative ways of solving these problems are the proximal DC algorithms, which require that the convex part of the objective function have L -smoothness. In this article,...

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Vydané v:	Computational optimization and applications Ročník 83; číslo 3; s. 893 - 931
Hlavní autori:	Takahashi, Shota, Fukuda, Mituhiro, Tanaka, Mirai
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.12.2022 Springer Nature B.V
Predmet:	Algorithms Convex and Discrete Geometry Critical point Management Science Mathematics Mathematics and Statistics Operations Research Operations Research/Decision Theory Optimization Phase retrieval Smoothness Statistics Kurdyka-Łojasiewicz inequality Nonconvex optimization 90C30 65K05 Nonsmooth optimization 90C26 Bregman proximal DC algorithms Difference-of-convex optimization Bregman distances
ISSN:	0926-6003, 1573-2894
On-line prístup:	Získať plný text
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