A non-convex piecewise quadratic approximation of ℓ0 regularization: theory and accelerated algorithm

Non-convex regularization has been recognized as an especially important approach in recent studies to promote sparsity. In this paper, we study the non-convex piecewise quadratic approximation (PQA) regularization for sparse solutions of the linear inverse problem. It is shown that exact recovery o...

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Bibliographic Details
Published in:	Journal of global optimization Vol. 86; no. 2; pp. 323 - 353
Main Authors:	Li, Qian, Zhang, Wei, Bai, Yanqin, Wang, Guoqiang
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.06.2023 Springer Nature B.V
Subjects:	Algorithms Approximation Compressibility Computer Science Convergence Inverse problems Iterative methods Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Real Functions Recovery Regularization Sparsity Exact recovery Sparsity optimization 65K05 Non-convex approximation Accelerated gradient algorithm 90C06 Iterative thresholding algorithm 90C26
ISSN:	0925-5001, 1573-2916
Online Access:	Get full text
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