Motivated by problems in optimization we study the sparsity of the solutions to systems of linear Diophantine equations and linear integer programs, i.e., the number of non-zero entries of a solution, which is often referred to as the ℓ0-norm. Our main results are improved bounds on the ℓ0-norm of sparse solutions to systems Ax=b, where A∈Zm×n, b∈Zm and x is either a general integer vector (lattice case) or a non-negative integer vector (semigroup case). In the lattice case and certain scenarios of the semigroup case, we give polynomial time algorithms for computing solutions with ℓ0-norm satisfying the obtained bounds
AbstractWe consider the problem of approximate solution x̄ of of a linear system Ax = b over the rea...
In exact sparse optimization problems on Rd (also known as sparsity constrained problems), one looks...
We study the thresholds for the property of containing a solution to a linear homogeneous system in ...
We present structural results on solutions to the Diophantine system Ay = b, y ∈ Z t ≥0 with the ...
We examine how sparse feasible solutions of integer programs are, on average. Average case here mean...
International audienceThe paper deals with the problem of finding sparse solutions to systems of pol...
We propose a new algorithm to solve sparse linear systems of equations over the integers. This algor...
We present structural results on solutions to the Diophantine system $A{\boldsymbol y} = {\...
\u3cp\u3eThis paper considers integer formulations of binary sets X of minimum sparsity, i.e., the m...
20 pages, Corollary 6.1 has been correctedInternational audienceToric (or sparse) elimination theory...
AbstractWe present a condition on the matrix of an underdetermined linear system which guarantees th...
The optimization models with sparsity arise in many areas of science and engineering, such as compre...
Sparse approximation aims to fit a linear model in a least-squares sense, with a small number of non-...
International audienceLet $A$ be a matrix of size $M\times N$ (a dictionary) and let $\|.\|$ be a no...
AbstractA randomized algorithm is given for solving a system of linear equations over a principal id...
AbstractWe consider the problem of approximate solution x̄ of of a linear system Ax = b over the rea...
In exact sparse optimization problems on Rd (also known as sparsity constrained problems), one looks...
We study the thresholds for the property of containing a solution to a linear homogeneous system in ...
We present structural results on solutions to the Diophantine system Ay = b, y ∈ Z t ≥0 with the ...
We examine how sparse feasible solutions of integer programs are, on average. Average case here mean...
International audienceThe paper deals with the problem of finding sparse solutions to systems of pol...
We propose a new algorithm to solve sparse linear systems of equations over the integers. This algor...
We present structural results on solutions to the Diophantine system $A{\boldsymbol y} = {\...
\u3cp\u3eThis paper considers integer formulations of binary sets X of minimum sparsity, i.e., the m...
20 pages, Corollary 6.1 has been correctedInternational audienceToric (or sparse) elimination theory...
AbstractWe present a condition on the matrix of an underdetermined linear system which guarantees th...
The optimization models with sparsity arise in many areas of science and engineering, such as compre...
Sparse approximation aims to fit a linear model in a least-squares sense, with a small number of non-...
International audienceLet $A$ be a matrix of size $M\times N$ (a dictionary) and let $\|.\|$ be a no...
AbstractA randomized algorithm is given for solving a system of linear equations over a principal id...
AbstractWe consider the problem of approximate solution x̄ of of a linear system Ax = b over the rea...
In exact sparse optimization problems on Rd (also known as sparsity constrained problems), one looks...
We study the thresholds for the property of containing a solution to a linear homogeneous system in ...