An inertial proximal splitting method with applications

In this paper, we propose an inertial proximal splitting method for solving the non-convex optimization problem, and the new method employs the idea of inertial proximal point to improve the computational efficiency. Based on the assumptions that the sequence generated by the new method is bounded a...

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Bibliographic Details
Published inOptimization Vol. 73; no. 8; pp. 2555 - 2584
Main Authors Wang, Xiaoquan, Shao, Hu, Liu, Pengjie, Yang, Wenli
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 02.08.2024
Taylor & Francis LLC
Subjects
Convexity
global convergence
Image processing
inertial proximal point method
Kurdyka-Łojasiewicz property
Multi-block non-convex optimization
Splitting
splitting method
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Summary:In this paper, we propose an inertial proximal splitting method for solving the non-convex optimization problem, and the new method employs the idea of inertial proximal point to improve the computational efficiency. Based on the assumptions that the sequence generated by the new method is bounded and the auxiliary function satisfies the Kurdyka-Łojasiewicz property, the global convergence analysis with a more relaxed parameter range is proved for the proposed method. Moreover, some numerical results on SCAD, image processing and robust PCA non-convex problems are tested to demonstrate the effectiveness and superiority of the proposed method.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:0233-1934
1029-4945
DOI:10.1080/02331934.2023.2230994