The following pages link to Decoding by Linear Programming (Q3546644):
Displaying 50 items.
- The restricted isometry property and its implications for compressed sensing (Q927127) (← links)
- A remark on compressed sensing (Q941909) (← links)
- Sparse approximate solution of partial differential equations (Q972312) (← links)
- Sparse recovery by non-convex optimization - instance optimality (Q984656) (← links)
- A note on guaranteed sparse recovery via \(\ell_1\)-minimization (Q984666) (← links)
- High-dimensional Gaussian model selection on a Gaussian design (Q985331) (← links)
- The benefit of group sparsity (Q987996) (← links)
- Lasso-type recovery of sparse representations for high-dimensional data (Q1002157) (← links)
- Chirp sensing codes: Deterministic compressed sensing measurements for fast recovery (Q1006638) (← links)
- CoSaMP: Iterative signal recovery from incomplete and inaccurate samples (Q1012549) (← links)
- Sparsest solutions of underdetermined linear systems via \( \ell _q\)-minimization for \(0<q\leqslant 1\) (Q1012556) (← links)
- Uniform uncertainty principle and signal recovery via regularized orthogonal matching pursuit (Q1029209) (← links)
- Random sampling of sparse trigonometric polynomials. II: Orthogonal matching pursuit versus basis pursuit (Q1029548) (← links)
- Random projections of smooth manifolds (Q1029551) (← links)
- Sparse solutions to underdetermined Kronecker product systems (Q1039753) (← links)
- A simple proof of the restricted isometry property for random matrices (Q1039884) (← links)
- Uniform uncertainty principle for Bernoulli and subgaussian ensembles (Q1039886) (← links)
- Signal recovery under cumulative coherence (Q1624658) (← links)
- Secure estimation based Kalman filter for cyber-physical systems against sensor attacks (Q1626921) (← links)
- On the post selection inference constant under restricted isometry properties (Q1627565) (← links)
- Gaussian polytopes: a cumulant-based approach (Q1635836) (← links)
- Observable dictionary learning for high-dimensional statistical inference (Q1639590) (← links)
- A primal-dual homotopy algorithm for \(\ell _{1}\)-minimization with \(\ell _{\infty }\)-constraints (Q1639715) (← links)
- Sparse approximate solution of fitting surface to scattered points by MLASSO model (Q1656898) (← links)
- Compressed sensing for real measurements of quaternion signals (Q1661251) (← links)
- Sparsity and independence: balancing two objectives in optimization for source separation with application to fMRI analysis (Q1661463) (← links)
- Compressed sensing of data with a known distribution (Q1669057) (← links)
- Expander \(\ell_0\)-decoding (Q1669068) (← links)
- \(l_{0}\)-norm based structural sparse least square regression for feature selection (Q1669627) (← links)
- Recovery of block sparse signals under the conditions on block RIC and ROC by BOMP and BOMMP (Q1673807) (← links)
- Relaxed sparse eigenvalue conditions for sparse estimation via non-convex regularized regression (Q1677029) (← links)
- Restricted Robinson constraint qualification and optimality for cardinality-constrained cone programming (Q1682972) (← links)
- Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions (Q1683689) (← links)
- The matrix splitting based proximal fixed-point algorithms for quadratically constrained \(\ell_{1}\) minimization and Dantzig selector (Q1686207) (← links)
- Analysis of the equivalence relationship between \(l_{0}\)-minimization and \(l_{p}\)-minimization (Q1688516) (← links)
- Online fault diagnosis for nonlinear power systems (Q1689341) (← links)
- Exact recovery of sparse multiple measurement vectors by \(l_{2,p}\)-minimization (Q1691327) (← links)
- A hierarchical framework for recovery in compressive sensing (Q1693135) (← links)
- Sparse blind deconvolution and demixing through \(\ell_{1,2}\)-minimization (Q1696370) (← links)
- Deterministic construction of compressed sensing matrices based on semilattices (Q1698065) (← links)
- Hybrid reconstruction of quantum density matrix: when low-rank meets sparsity (Q1698802) (← links)
- A Rice method proof of the null-space property over the Grassmannian (Q1700392) (← links)
- A sharp recovery condition for block sparse signals by block orthogonal multi-matching pursuit (Q1700711) (← links)
- Random matrices and erasure robust frames (Q1704861) (← links)
- A group adaptive elastic-net approach for variable selection in high-dimensional linear regression (Q1705570) (← links)
- Learning data discretization via convex optimization (Q1707483) (← links)
- Sparsity and incoherence in orthogonal matching pursuit (Q1710949) (← links)
- Linear regression with sparsely permuted data (Q1711600) (← links)
- Optimization methods for regularization-based ill-posed problems: a survey and a multi-objective framework (Q1712546) (← links)
- Fused Lasso penalized least absolute deviation estimator for high dimensional linear regression (Q1713210) (← links)
