## A Slightly Lifted Convex Relaxation for Nonconvex Quadratic Programming with Ball Constraints

\(\) Globally optimizing a nonconvex quadratic over the intersection of \(m\) balls in \(\mathbb{R}^n\) is known to be polynomial-time solvable for fixed \(m\). Moreover, when \(m=1\), the standard semidefinite relaxation is exact, and when \(m=2\), it has recently been shown that an exact relaxation can be constructed via a disjunctive semidefinite formulation based on essentially two copies of the \(m=1\) case. … Read more