Group Sparse Recovery via the $\ell ^0(\ell ^2)$ Penalty: Theory and Algorithm

DOI10.1109/TSP.2016.2630028zbMath1414.94280arXiv1601.04174MaRDI QIDQ4620615

Bangti Jin, Xiliang Lu, Yu Ling Jiao

Publication date: 8 February 2019

Published in: IEEE Transactions on Signal Processing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1601.04174

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Related Items (11)

GSDAR: a fast Newton algorithm for \(\ell_0\) regularized generalized linear models with statistical guarantee ⋮ Difference-of-Convex Algorithms for a Class of Sparse Group $\ell_0$ Regularized Optimization Problems ⋮ Solving constrained nonsmooth group sparse optimization via group Capped-\(\ell_1\) relaxation and group smoothing proximal gradient algorithm ⋮ Solution sets of three sparse optimization problems for multivariate regression ⋮ A primal dual active set with continuation algorithm for high-dimensional nonconvex SICA-penalized regression ⋮ A greedy Newton-type method for multiple sparse constraint problem ⋮ Unnamed Item ⋮ A perturbation analysis based on group sparse representation with orthogonal matching pursuit ⋮ Variable selection via generalized SELO-penalized Cox regression models ⋮ Computation of second-order directional stationary points for group sparse optimization ⋮ Group Sparse Optimization for Images Recovery Using Capped Folded Concave Functions

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