We study (nonconvex) quadratic optimization problems with complementarity constraints,
establishing an exact completely positive reformulation under—apparently new—mild …

This paper proposes a new second-order cone programming (SOCP) relaxation for convex
quadratic programs with linear complementarity constraints. The new SOCP relaxation is …

The indefinite separable quadratic knapsack problem (ISQKP) with box constraints is known
to be NP-hard. In this paper, we propose a new branch-and-bound algorithm based on a …

This paper proposes a second-order cone programming (SOCP) relaxation for the
generalized trust-region problem by exploiting the property that any symmetric matrix and …

We present a new second order cone programming (SOCP) relaxation of nonconvex
quadratic programs with a few negative eigenvalues (NQP-r-NE) by employing the …

Quadratic programs with complementarity constraints (QPCC) are NP-hard due to the
nonconvexity of complementarity relation between the pairs of nonnegative variables. Most …

In this paper, we develop a new deflationary blind source extraction (BSE) algorithm that
extracts source signals in a sequential fashion via the joint generalized eigenvectors of a set …

In this paper, we propose a novel low-dimensional semidefinite programming (SDP)
relaxation for convex quadratically constrained nonconvex quadratic programming …

We study (nonconvex) quadratic optimization problems with complementarity constraints,
establishing an exact completely positive reformulation under—apparently new—mild …