The ellipsoid method is an algorithm that solves the (weak) feasibility and linear optimization problems for convex sets by making oracle calls to their (weak) separation problem. We observe that the previously known method for showing that this reduction can be done in fixed-point logic with counting (FPC) for linear and semidefinite programs applies to any family of explicitly bounded convex sets. We use this observation to show that the exact feasibility problem for semidefinite programs is expressible in the infinitary version of FPC. As a corollary we get that, for the isomorphism problem, the Lasserre/Sums-of-Squares semidefinite programming hierarchy of relaxations collapses to the Sherali-Adams linear programming hierarchy, up to a ...
We establish the expressibility in fixed-point logic with counting (FPC) of a number of natural poly...
International audienceLet A 0 ,. .. , A n be m × m symmetric matrices with entries in Q, and let A(x...
A hierarchy of convex relaxations for semialgebraic problems is introduced. For questions reducible ...
The ellipsoid method is an algorithm that solves the (weak) feasibility and linear optimization prob...
The ellipsoid method is an algorithm that solves the (weak) feasibility and linear optimization prob...
The ellipsoid method is an algorithm that solves the (weak) feasibility and linear optimization prob...
We show that the ellipsoid method for solving linear programs can be implemented in a way that respe...
We show that the ellipsoid method for solving semidefinite programs (SDPs) can be expressed in fixed...
An exact semidefinite linear programming (SDP) relaxation of a nonlinear semidef-inite programming p...
Linear programming (LP) and semidefinite programming (SDP) are among the most important tools in Ope...
AbstractWe address the exact semidefinite programming feasibility problem (SDFP) consisting in check...
Semidefinite Programming (SDP) is a class of convex optimization problems with a linear objective fu...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Comp...
We consider the general feasibility problem for semidefinite programming: Determine whether a given ...
International audienceLet A 0 ,. .. , A n be m × m symmetric matrices with entries in Q, and let A(x...
We establish the expressibility in fixed-point logic with counting (FPC) of a number of natural poly...
International audienceLet A 0 ,. .. , A n be m × m symmetric matrices with entries in Q, and let A(x...
A hierarchy of convex relaxations for semialgebraic problems is introduced. For questions reducible ...
The ellipsoid method is an algorithm that solves the (weak) feasibility and linear optimization prob...
The ellipsoid method is an algorithm that solves the (weak) feasibility and linear optimization prob...
The ellipsoid method is an algorithm that solves the (weak) feasibility and linear optimization prob...
We show that the ellipsoid method for solving linear programs can be implemented in a way that respe...
We show that the ellipsoid method for solving semidefinite programs (SDPs) can be expressed in fixed...
An exact semidefinite linear programming (SDP) relaxation of a nonlinear semidef-inite programming p...
Linear programming (LP) and semidefinite programming (SDP) are among the most important tools in Ope...
AbstractWe address the exact semidefinite programming feasibility problem (SDFP) consisting in check...
Semidefinite Programming (SDP) is a class of convex optimization problems with a linear objective fu...
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Comp...
We consider the general feasibility problem for semidefinite programming: Determine whether a given ...
International audienceLet A 0 ,. .. , A n be m × m symmetric matrices with entries in Q, and let A(x...
We establish the expressibility in fixed-point logic with counting (FPC) of a number of natural poly...
International audienceLet A 0 ,. .. , A n be m × m symmetric matrices with entries in Q, and let A(x...
A hierarchy of convex relaxations for semialgebraic problems is introduced. For questions reducible ...