Adaptive projected gradient thresholding methods for constrained \(l_0\) problems
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Publication:892792
DOI10.1007/s11425-015-5038-9zbMath1327.90393OpenAlexW2259617914MaRDI QIDQ892792
Xiang-Yang Li, Feng-Min Xu, Zhihua Zhao
Publication date: 12 November 2015
Published in: Science China. Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s11425-015-5038-9
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Cites Work
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- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- Iterative hard thresholding for compressed sensing
- CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
- A hybrid optimization approach to index tracking
- Least angle regression. (With discussion)
- Pathwise coordinate optimization
- An efficient optimization approach for a cardinality-constrained index tracking problem
- Optimality Conditions and a Smoothing Trust Region Newton Method for NonLipschitz Optimization
- On the convergence of an active-set method for ℓ1minimization
- A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation
- Lower Bound Theory of Nonzero Entries in Solutions of $\ell_2$-$\ell_p$ Minimization
- Hard Thresholding Pursuit: An Algorithm for Compressive Sensing
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
- Atomic Decomposition by Basis Pursuit
- An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
- Cardinality versusq-norm constraints for index tracking
- Sparse Solution of Underdetermined Systems of Linear Equations by Stagewise Orthogonal Matching Pursuit
- Non-Lipschitz $\ell_{p}$-Regularization and Box Constrained Model for Image Restoration
- Sparse Approximation via Penalty Decomposition Methods
- Stable signal recovery from incomplete and inaccurate measurements
- Compressed sensing