: Nowadays, solving nonsmooth (not necessarily differentiable) optimization problems plays a very important role in many areas of industrial applications. Most of the algorithms d...
Abstract. We propose a BFGS primal-dual interior point method for minimizing a convex function on a convex set defined by equality and inequality constraints. The algorithm generat...
Paul Armand, Jean Charles Gilbert, Sophie Jan-J&ea...
Graph transduction methods label input data by learning a classification function that is regularized to exhibit smoothness along a graph over labeled and unlabeled samples. In pr...
Markov random fields with higher order potentials have emerged as a powerful model for several problems in computer vision. In order to facilitate their use, we propose a new rep...
We study the problem of minimizing a sum of p-norms where p is a fixed real number in the interval [1, ]. Several practical algorithms have been proposed to solve this problem. How...