MINLP problems are hard constrained optimization problems, with nonlinear constraints and mixed discrete continuous variables. They can be solved using a Branch-and-Bound scheme c...
Given a positive integer n and a positive semidefinite matrix A = (Aij ) ∈ Rm×m the positive semidefinite Grothendieck problem with rank-nconstraint is (SDPn) maximize mX i=1 ...
Abstract. We present a new algorithm for approximate joint diagonalization of several symmetric matrices. While it is based on the classical least squares criterion, a novel intrin...
We introduce an extension of linear constraints, called linearrange constraints, which allows for (meta-)reasoning about the approximation width of variables. Semantics for linear...
Max-SAT-CC is the following optimization problem: Given a formula in CNF and a bound k, find an assignment with at most k variables being set to true that maximizes the number of ...