A new approach based on Estimation Distribution Algorithms for constrained multiobjective shape optimization is proposed in this article. Pareto dominance and feasibility rules ar...
Abstract. In this paper we unify divergence minimization and statistical inference by means of convex duality. In the process of doing so, we prove that the dual of approximate max...
Abstract--This paper deals with the reconstruction of T1-T2 correlation spectra in nuclear magnetic resonance relaxometry. The ill-posed character and the large size of this invers...
This paper deals with video segmentation based on motion and spatial information. Classically, the nucleus of the motion term is the motion compensation error (MCE) between two con...
Ariane Herbulot, Sylvain Boltz, Eric Debreuve, Mic...
Various supervised inference methods can be analyzed as convex duals of the generalized maximum entropy (MaxEnt) framework. Generalized MaxEnt aims to find a distribution that max...