Proximal Linearized Iteratively Reweighted Algorithms for Nonconvex and Nonsmooth Optimization Problem

The nonconvex and nonsmooth optimization problem has been attracting increasing attention in recent years in image processing and machine learning research. The algorithm-based reweighted step has been widely used in many applications. In this paper, we propose a new, extended version of the iterati...

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Detalles Bibliográficos

Autores principales:	Juyeb Yeo, Myeongmin Kang
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	MDPI AG 2022-04-01
Colección:	Axioms
Materias:	iterative reweighted algorithm linearization nonconvex optimization nonsmooth objective function Kurdyka–Łojasiewicz property
Acceso en línea:	https://www.mdpi.com/2075-1680/11/5/201
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