An unbiased approach to compressed sensing (Q5132273)

scientific article; zbMATH DE number 7272201

Language	Label	Description	Also known as
English	An unbiased approach to compressed sensing	scientific article; zbMATH DE number 7272201

Statements

instance of

scholarly article

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title

An unbiased approach to compressed sensing (English)

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10 November 2020

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full work available at URL

https://arxiv.org/abs/1806.05283

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zbMATH Keywords

compressed sensing

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regularization

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non-convex optimization

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non-smooth optimization

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describes a project that uses

PDCO

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sparsenet

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MaRDI profile type

MaRDI publication profile

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cites work

Generalized sampling and infinite-dimensional compressed sensing

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BREAKING THE COHERENCE BARRIER: A NEW THEORY FOR COMPRESSED SENSING

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Convex envelopes for fixed rank approximation

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Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward-backward splitting, and regularized Gauss-Seidel methods

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Convex analysis and monotone operator theory in Hilbert spaces

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Compressed Sensing: How Sharp Is the Restricted Isometry Property?

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Iterative thresholding for sparse approximations

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Iterative hard thresholding for compressed sensing

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Minimization of non-smooth, non-convex functionals by iterative thresholding

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Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection

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The restricted isometry property and its implications for compressed sensing

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Robust principal component analysis?

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Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information

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Stable signal recovery from incomplete and inaccurate measurements

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Decoding by Linear Programming

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On convex envelopes and regularization of non-convex functionals without moving global minima

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Atomic Decomposition by Basis Pursuit

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Signal Recovery by Proximal Forward-Backward Splitting

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For most large underdetermined systems of linear equations the minimal 𝓁<sub>1</sub>‐norm solution is also the sparsest solution

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Stable recovery of sparse overcomplete representations in the presence of noise

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Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties

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Nonconcave penalized likelihood with a diverging number of parameters.

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Strong oracle optimality of folded concave penalized estimation

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A mathematical introduction to compressive sensing

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Convex low rank approximation

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Support recovery without incoherence: a case for nonconvex regularization

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<i>SparseNet</i>: Coordinate Descent With Nonconvex Penalties

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Sparse Approximate Solutions to Linear Systems

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

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Description of the Minimizers of Least Squares Regularized with $\ell_0$-norm. Uniqueness of the Global Minimizer

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Relationship between the optimal solutions of least squares regularized with $\ell_{0}$-norm and constrained by $k$-sparsity

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Relaxed sparse eigenvalue conditions for sparse estimation via non-convex regularized regression

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Q5694963

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A Continuous Exact $\ell_0$ Penalty (CEL0) for Least Squares Regularized Problem

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Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)

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Sparse Regularization via Convex Analysis

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Global convergence of ADMM in nonconvex nonsmooth optimization

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Optimal computational and statistical rates of convergence for sparse nonconvex learning problems

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Nearly unbiased variable selection under minimax concave penalty

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A general theory of concave regularization for high-dimensional sparse estimation problems

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One-step sparse estimates in nonconcave penalized likelihood models

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Identifiers

zbMATH Open document ID

1458.94080

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DOI

10.1088/1361-6420/abbd7f

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Mathematics Subject Classification ID

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Sitelinks

Mathematics(1 entry)

mardi Publication:5132273