An Iterative Threshold Algorithm of Log-sum Regularization for Sparse Problem
The log-sum function as a penalty has always been drawing widespread attention in the field of sparse problems. However, it brings a non-convex, non-smooth and non-Lipschitz optimization problem that is difficult to tackle. To overcome the problem, an iterative threshold algorithm for the sparse opt...
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Published in | IEEE transactions on circuits and systems for video technology Vol. 33; no. 9; p. 1 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
New York
IEEE
01.09.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | The log-sum function as a penalty has always been drawing widespread attention in the field of sparse problems. However, it brings a non-convex, non-smooth and non-Lipschitz optimization problem that is difficult to tackle. To overcome the problem, an iterative threshold algorithm for the sparse optimization problems with log-sum function is proposed in this paper. For brevity, the sparse optimization problems with log-sum function are named log-sum regularization. Firstly, by introducing an intermediate function to construct another new function, a property theorem about solution for log-sum regularization is established. Secondly, based on the above theorem, the optimal setting rules of the compromising parameters are elaborated, and an iterative log-sum threshold algorithm is proposed. Thirdly, under the situation that the compromising parameters of log-sum regularization are relatively small, it can be proven that the proposed algorithm converges to a local minimizer of log-sum regularization. Finally, a series of simulations are implemented to examine performance of the proposed algorithm, and the results exhibit that the proposed algorithm outperforms the state-of-the-art algorithms. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
ISSN: | 1051-8215 1558-2205 |
DOI: | 10.1109/TCSVT.2023.3247944 |