Optimal Transport in machine learning with application to Domain Adaptation

Apparaît dans la collection : GDR ISIS - Transport Optimal et Apprentissage Statistique

In this talk, I will present the role that optimal transport can play within the context of machine learning, as optimal transport (OT) theory provides geometric tools to compare probability measures. After a brief introduction on the basics of OT, I will describe how they can be applied in domain adaptation and representation learning context.