Add to ORKGWe study the thresholds for the property of containing a solution to a linear homogeneous system in random sets. We expand a previous sparse Sz\'emeredi-type result of Schacht to the broadest class of matrices possible. We also provide a shorter proof of a sparse Rado result of Friedgut, R
Abstract—Many sparse approximation algorithms accurately recover the sparsest solution to an underde...
International audienceA series of recent results shows that if a signal admits a sufficiently sparse...
We derive Concentration of Measure (CoM) inequalities for randomized Toeplitz matrices. These inequa...
We study the thresholds for the property of containing a solution to a linear homogeneous system in ...
A common theme in modern combinatorics consists in proving sparse analogues of results known in the ...
A vector with at most k nonzeros is called k-sparse. We show that enumerating the support vectors of...
We give a new theoretical tool to solve sparse systems with finitely many solutions. It is based on ...
International audienceFor an m×N underdetermined system of linear equations with independent pre-Gau...
For an m × N underdetermined system of linear equations with independent pre-Gaussian random coeffic...
We consider the binomial random set model $[n]_p$ where each element in $\{1,\dots,n\}$ is chosen in...
International audienceLet A be an nxm matrix with m>n, and suppose that the underdetermined linear s...
Abstract—Recently, the worse-case analysis, probabilistic anal-ysis and empirical justification have...
We study sparse recovery with structured random measurement matrices having independent, identically...
We consider the problem of approximate solution ex of a linear system Ax = b over the reals, such th...
We consider inexact linear equations y ≈ Φα where y is a given vector in R n, Φ is a given n by m ma...
Abstract—Many sparse approximation algorithms accurately recover the sparsest solution to an underde...
International audienceA series of recent results shows that if a signal admits a sufficiently sparse...
We derive Concentration of Measure (CoM) inequalities for randomized Toeplitz matrices. These inequa...
We study the thresholds for the property of containing a solution to a linear homogeneous system in ...
A common theme in modern combinatorics consists in proving sparse analogues of results known in the ...
A vector with at most k nonzeros is called k-sparse. We show that enumerating the support vectors of...
We give a new theoretical tool to solve sparse systems with finitely many solutions. It is based on ...
International audienceFor an m×N underdetermined system of linear equations with independent pre-Gau...
For an m × N underdetermined system of linear equations with independent pre-Gaussian random coeffic...
We consider the binomial random set model $[n]_p$ where each element in $\{1,\dots,n\}$ is chosen in...
International audienceLet A be an nxm matrix with m>n, and suppose that the underdetermined linear s...
Abstract—Recently, the worse-case analysis, probabilistic anal-ysis and empirical justification have...
We study sparse recovery with structured random measurement matrices having independent, identically...
We consider the problem of approximate solution ex of a linear system Ax = b over the reals, such th...
We consider inexact linear equations y ≈ Φα where y is a given vector in R n, Φ is a given n by m ma...
Abstract—Many sparse approximation algorithms accurately recover the sparsest solution to an underde...
International audienceA series of recent results shows that if a signal admits a sufficiently sparse...
We derive Concentration of Measure (CoM) inequalities for randomized Toeplitz matrices. These inequa...