We propose a convex-concave programming approach for the labeled weighted graph matching problem. The convex-concave programming formulation is obtained by rewriting the graph matching problem as a least-square problem on the set of permutation matrices and relaxing it to two different optimization problems: a quadratic convex and a quadratic concave optimization problem on the set of doubly st...

We present in this paper some results for solving the Quadratic Eigenvalue Complementarity Problem (QEiCP) by using DC(Difference of Convex functions) programming approaches. Two equivalent Nonconvex Polynomial Programming (NLP) formulations of QEiCP are introduced. We focus on the construction of the DC programming formulations of the QEiCP from these NLPs. The corresponding numerical solution...

We study the problem of variable selection in convex nonparametric regression. Under the assumption that the true regression function is convex and sparse, we develop a screening procedure to select a subset of variables that contains the relevant variables. Our approach is a two-stage quadratic programming method that estimates a sum of one-dimensional convex functions, followed by one-dimensi...

Let F be a quadratically constrained, possibly nonconvex, bounded set, and let E1, . . . , El denote ellipsoids contained in F with non-intersecting interiors. We prove that minimizing an arbitrary quadratic q(·) over G := F\∪k=1 int(Ek) is no more difficult than minimizing q(·) over F in the following sense: if a given semidefinite-programming (SDP) relaxation for min{q(x) : x ∈ F} is tight, t...

This paper is concerned with multi-period sequential decision problems for financial asset allocation. A model is proposed in which periodic optimal portfolio adjustments are determined with the objective of minimizing a cumulative risk measure over the investment horizon, while satisfying portfolio diversity constraints at each period and achieving or exceeding a desired terminal expected weal...

This paper introduces the research status of convex quadratic bilevel programming at present firstly. Secondly, it analyzes the problem of convex quadratic bilevel programming models, concepts and properties. On this basis, using the optimality conditions of KKT, the problem will be transformed into a single complementary slackness relaxation problem. To solve this problem, we propose an orthog...

Clifford A. Meyer and Christodoulos A. Floudas Department of Chemical Engineering, Princeton University, Princeton, NJ 08544, USA Abstract This paper presents an efficient branch and bound approach to address the global optimization of constrained optimization problems with twice differentiable functions. A lower bound on the global minimum is determined via a convex nonlinear programming probl...