54 citations · 92 across the 14 of their papers we have counts for
5 papers · 1 filter
Trust--Region Problems with Linear Inequality Constraints: Exact SDP Relaxation, Global Optimality and Robust Optimization
V. Jeyakumar, G. Li
The trust-region problem, which minimizes a nonconvex quadratic function over a ball, is a key subproblem in trust-region methods for solving nonlinear optimization problems. It en…
SDP Duals without Duality Gaps for a Class of Convex Minimax Programs
V. Jeyakumar, J. Vicente-Perez
In this paper we introduce a new dual program, which is representable as a semi-definite linear programming problem, for a primal convex minimax programming model problem and show…
Robust SOS-Convex Polynomial Programs: Exact SDP Relaxations
V. Jeyakumar, G. Li, J. Vicente-Perez
This paper studies robust solutions and semidefinite linear programming (SDP) relaxations of a class of convex polynomial programs in the face of data uncertainty. The class of con…
Convergence of the Lasserre Hierarchy of SDP Relaxations for Convex Polynomial Programs without Compactness
V. Jeyakumar, T. S. Pham, G. Li
The Lasserre hierarchy of semidefinite programming (SDP) relaxations is an effective scheme for finding computationally feasible SDP approximations of polynomial optimization over…
On Polynomial Optimization over Non-compact Semi-algebraic Sets
Vaithilingam Jeyakumar, Jean-Bernard Lasserre, G. Li
We consider the class of polynomial optimization problems for which the quadratic module generated by the polynomials that define and the polynomial $c-f…