New regularization method and iteratively reweighted algorithm for sparse vector recovery (Q2033724)

scientific article; zbMATH DE number 7360565

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English	New regularization method and iteratively reweighted algorithm for sparse vector recovery	scientific article; zbMATH DE number 7360565

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instance of

scholarly article

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title

New regularization method and iteratively reweighted algorithm for sparse vector recovery (English)

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AMM. Applied Mathematics and Mechanics. (English Edition)

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publication date

17 June 2021

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zbMATH Keywords

regularization method

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iteratively reweighted algorithm (IR-algorithm)

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sparse vector recovery

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MaRDI profile type

Publication

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full work available at URL

https://doi.org/10.1007/s10483-020-2561-6

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cites work

Q5515676

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Higher order convergence rates for Bregman iterated variational regularization of inverse problems

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An Efficient Proximity Point Algorithm for Total-Variation-Based Image Restoration

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Total variation regularization of multi-material topology optimization

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Nuclear norm regularization with a low-rank constraint for matrix completion

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First-order optimality condition of basis pursuit denoise problem

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Proximity point algorithm for low-rank matrix recovery from sparse noise corrupted data

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Regularization with non-convex separable constraints

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Sparse regularization with <i> l <sup>q</sup> </i> penalty term

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Generalized sparse recovery model and its neural dynamical optimization method for compressed sensing

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Restricted isometry properties and nonconvex compressive sensing

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A note on the complexity of $L _{p }$ minimization

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Sparsest solutions of underdetermined linear systems via $ \ell _q$-minimization for $0<q\leqslant 1$

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A note on guaranteed sparse recovery via $\ell_1$-minimization

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A Probabilistic and RIPless Theory of Compressed Sensing

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Sparse Approximation Property and Stable Recovery of Sparse Signals From Noisy Measurements

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Enhancing sparsity by reweighted $\ell _{1}$ minimization

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Iteratively reweighted least squares minimization for sparse recovery

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Minimizing Nonconvex Functions for Sparse Vector Reconstruction

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Lower Bound Theory of Nonzero Entries in Solutions of $\ell_2$-$\ell_p$ Minimization

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An Unconstrained $\ell_q$ Minimization with $0q\leq1$ for Sparse Solution of Underdetermined Linear Systems

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Elastic-net regularization in learning theory

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Elastic-net regularization: error estimates and active set methods

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Regularization and Variable Selection Via the Elastic Net

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Linearized Bregman iterations for compressed sensing

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Analysis and Generalizations of the Linearized Bregman Method

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A lower bound guaranteeing exact matrix completion via singular value thresholding algorithm

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Q4039929

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Theoretical foundations and numerical methods for sparse recovery. Papers based on the presentations of the summer school ``Theoretical foundations and numerical methods for sparse recovery'', Vienna, Austria, August 31 -- September 4, 2009.

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Identifiers

zbMATH Open document ID

1462.49047

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Mathematics Subject Classification ID

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10.1007/S10483-020-2561-6

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Sitelinks

Mathematics(1 entry)

mardi Publication:2033724