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20132026
most citedGlobal convergence of splitting methods for nonconvex composite optimization

316 citations · 903 across the 32 of their papers we have counts for

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5 papers · 1 filter

math.OC2013★ 1 cited

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…

math.OC2013★ 54 cited

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…

math.OC2013★ 1 cited

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…

math.FA2013★ 2 cited

Analysis of the convergence rate for the cyclic projection algorithm applied to basic semi-algebraic convex sets

Jonathan M. Borwein, Guoyin Li, Liangjin Yao

In this paper, we study the rate of convergence of the cyclic projection algorithm applied to finitely many basic semi-algebraic convex sets. We establish an explicit convergence r…

math.OC2013

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…