On the sparsity of Lasso minimizers in sparse data recovery
From MaRDI portal
Publication:2700886
DOI10.1007/s00365-022-09594-1OpenAlexW4304080612MaRDI QIDQ2700886
Eitan Tadmor, Simon Foucart, Ming Zhong
Publication date: 27 April 2023
Published in: Constructive Approximation (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2004.04348
inverse problemscompressive sensingdata recoveryrobust null space propertybasis pursuit denoising method
Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Random matrices (algebraic aspects) (15B52) Sampling theory in information and communication theory (94A20)
Related Items
Cites Work
- Unnamed Item
- Unnamed Item
- Nonlinear total variation based noise removal algorithms
- A mathematical introduction to compressive sensing
- Statistics for high-dimensional data. Methods, theory and applications.
- Explicit constructions of RIP matrices and related problems
- Instance-optimality in probability with an \(\ell _1\)-minimization decoder
- The restricted isometry property and its implications for compressed sensing
- Multiscale hierarchical decomposition of images with applications to deblurring, denoising, and segmentation
- Lasso-type recovery of sparse representations for high-dimensional data
- A simple proof of the restricted isometry property for random matrices
- False discoveries occur early on the Lasso path
- Least squares after model selection in high-dimensional sparse models
- Necessary and sufficient conditions of solution uniqueness in 1-norm minimization
- Simultaneous analysis of Lasso and Dantzig selector
- Bounds of restricted isometry constants in extreme asymptotics: formulae for Gaussian matrices
- The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
- Hierarchical Construction of Bounded Solutions in Critical Regularity Spaces
- Hierarchical Construction of Bounded Solutions of div U=F in Critical Regularity Spaces
- Sparse Recovery Algorithms: Sufficient Conditions in Terms of Restricted Isometry Constants
- On the Theorem of Uniform Recovery of Random Sampling Matrices
- Compressed sensing and best 𝑘-term approximation
- Improved Bounds on Restricted Isometry Constants for Gaussian Matrices
- Compressed Sensing: How Sharp Is the Restricted Isometry Property?
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- Sparse representations in unions of bases
- Greed is Good: Algorithmic Results for Sparse Approximation
- Singularity detection and processing with wavelets
- Atomic Decomposition by Basis Pursuit
- Uncertainty principles and ideal atomic decomposition
- Performance Analysis of Sparse Recovery Based on Constrained Minimal Singular Values
- A Multiscale Image Representation Using Hierarchical (BV,L2) Decompositions
- Sparse Representation of a Polytope and Recovery of Sparse Signals and Low-Rank Matrices
- Optimally sparse representation in general (nonorthogonal) dictionaries via ℓ 1 minimization
- Stable signal recovery from incomplete and inaccurate measurements
- Compressed sensing
