A Unified Bregman Alternating Minimization Algorithm for Generalized DC Programs with Application to Imaging

In this paper, we consider a class of nonconvex (not necessarily differentiable) optimization problems called generalized Difference-of-Convex functions (DC) programs, which is minimizing the sum of two separable DC parts and one two-block-variable coupling function. To circumvent the nonconvexity a...

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Vydané v:	Journal of scientific computing Ročník 101; číslo 3; s. 76
Hlavní autori:	He, Hongjin, Zhang, Zhiyuan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.12.2024 Springer Nature B.V
Predmet:	Algorithms Approximation Artificial intelligence Closed form solutions Computational Mathematics and Numerical Analysis Convexity Coupling Critical point First order algorithms Kernel functions Mathematical and Computational Engineering Mathematical and Computational Physics Mathematics Mathematics and Statistics Optimization Regularization Theoretical Variables Nonconvex optimization Kurdyka-Łojasiewicz property 90C30 Image processing 65K10 DC programs 90C26 49M37 Bregman distance First-order methods Alternating minimization algorithm
ISSN:	0885-7474, 1573-7691
On-line prístup:	Získať plný text
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