The proximity operator of the log-sum penalty
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Publication:2103448
DOI10.1007/s10915-022-02021-4OpenAlexW3134565505MaRDI QIDQ2103448
Ashley Prater-Bennette, Erin E. Tripp, Li-Xin Shen
Publication date: 13 December 2022
Published in: Journal of Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2103.02681
compressive sensingproximity operatorproximal mappingiteratively reweighted \(\ell_1\)log-sum functionlow-rank regularization
Uses Software
Cites Work
- Reduced rank regression via adaptive nuclear norm penalization
- Nearly unbiased variable selection under minimax concave penalty
- Enhancing sparsity by reweighted \(\ell _{1}\) minimization
- A trace inequality of John von Neumann
- Fast L1-L2 minimization via a proximal operator
- A proximal difference-of-convex algorithm with extrapolation
- Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward-backward splitting, and regularized Gauss-Seidel methods
- Structured sparsity promoting functions
- Image restoration: structured low rank matrix framework for piecewise smooth functions and beyond
- Majorization-Minimization Procedures and Convergence of SQP Methods for Semi-Algebraic and Tame Programs
- A Method for Finding Structured Sparse Solutions to Nonnegative Least Squares Problems with Applications
- iPiano: Inertial Proximal Algorithm for Nonconvex Optimization
- Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Compressive Sensing via Nonlocal Low-Rank Regularization
- Mixed Noise Removal via Laplacian Scale Mixture Modeling and Nonlocal Low-Rank Approximation
- Nonlocal low-rank regularized two-phase approach for mixed noise removal
- Minimization of $\ell_{1-2}$ for Compressed Sensing
- On Iteratively Reweighted Algorithms for Nonsmooth Nonconvex Optimization in Computer Vision
- FSIM: A Feature Similarity Index for Image Quality Assessment
- Convex analysis and monotone operator theory in Hilbert spaces
