UN MÉTODO EFICIENTE PARA RESOLVER UN PROBLEMA DE PROGRAMACIÓN CUADRÁTICA DERIVADO DEL APRENDIZAJE DE FUNCIONES DE DISTANCIA

Quadratic programming is a special type of the mathematical optimization problem. It is the problem of optimizing a quadratic function of several variables subject to linear constraints on these variables. When the number of constraints, as well as the number of variables are huge, the general method is not computational tractable. However, in some specic domain of application, we can take some advantages from the problem to improve performance of optimization process. The main idea of this work is to propose a new approach to solve a special quadratic program with large scale constraints, which is formulated to solve a problem of distance metric learning.