Pages that link to "Item:Q664941"

The following pages link to A necessary and sufficient condition for exact sparse recovery by \(\ell_1\) minimization (Q664941):

Displaying 24 items.

• Sharp support recovery from noisy random measurements by \(\ell_1\)-minimization (Q427066) (← links)
• On the solution uniqueness characterization in the L1 norm and polyhedral gauge recovery (Q511961) (← links)
• On verifiable sufficient conditions for sparse signal recovery via \(\ell_{1}\) minimization (Q633105) (← links)
• Verifiable conditions of \(\ell_{1}\)-recovery for sparse signals with sign restrictions (Q633107) (← links)
• Optimal dual certificates for noise robustness bounds in compressive sensing (Q892815) (← links)
• An LP empirical quadrature procedure for parametrized functions (Q1681553) (← links)
• Exact recovery of sparse multiple measurement vectors by \(l_{2,p}\)-minimization (Q1691327) (← links)
• Spark-level sparsity and the \(\ell_1\) tail minimization (Q1748258) (← links)
• The Lasso problem and uniqueness (Q1951165) (← links)
• The generalized Lasso problem and uniqueness (Q2002568) (← links)
• In defense of the indefensible: a very naïve approach to high-dimensional inference (Q2075709) (← links)
• The sparsity of LASSO-type minimizers (Q2105124) (← links)
• Necessary and sufficient conditions of solution uniqueness in 1-norm minimization (Q2260650) (← links)
• One condition for solution uniqueness and robustness of both \(\ell_1\)-synthesis and \(\ell_1\)-analysis minimizations (Q2374380) (← links)
• On a unified view of nullspace-type conditions for recoveries associated with general sparsity structures (Q2437335) (← links)
• \(\ell^1\)-analysis minimization and generalized (co-)sparsity: when does recovery succeed? (Q2659754) (← links)
• A necessary and sufficient condition for sparse vector recovery via \(\ell_1-\ell_2\) minimization (Q2667049) (← links)
• Exact Recoverability From Dense Corrupted Observations via $\ell _{1}$-Minimization (Q2989298) (← links)
• Necessary and Sufficient Conditions for Noiseless Sparse Recovery via Convex Quadratic Splines (Q3119537) (← links)
• Sparsest representations and approximations of an underdetermined linear system (Q4569345) (← links)
• Perfect Recovery Conditions for Non-negative Sparse Modeling (Q4620510) (← links)
• What is the Largest Sparsity Pattern That Can Be Recovered by 1-Norm Minimization? (Q5001600) (← links)
• Thresholding gradient methods in Hilbert spaces: support identification and linear convergence (Q5109200) (← links)
• A power analysis for Model-X knockoffs with \(\ell_p\)-regularized statistics (Q6136579) (← links)