A Unified Class of DC-type Convexity-Preserving Regularizers for Improved Sparse Regularization
Author:
Affiliation:
1. Tokyo Institute of Technology,Department of Information and Communications Engineering,Tokyo,Japan
Funder
JSPS
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9908519/9909515/09909805.pdf?arnumber=9909805
Reference23 articles.
1. Linearly-involved Moreau-Enhanced-over-Subspace Model: Debiased Sparse Modeling and Stable Outlier-Robust Regression;yukawa;ArXiv Preprint,2022
2. Sparse Image and Signal Processing
3. An Introduction to Total Variation for Image Analysis;chambolle;Theoretical Foundations and Numerical Methods for Sparse Recovery,2010
4. Proximal Splitting Methods in Signal Processing
5. Minimizing the Moreau Envelope of N onsmooth Convex Functions over the Fixed Point Set of Certain Quasi-Nonexpansive Mappings;yamada;Fixed-Point Algorithms For Inverse Problems in Science and Engineering,2011
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. A Unified Framework for Solving a General Class of Nonconvexly Regularized Convex Models;IEEE Transactions on Signal Processing;2023
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