Enregistré dans:
Détails bibliographiques
Auteurs principaux: Gallouët, Thomas O., Natale, Andrea, Todeschi, Gabriele
Format: Preprint
Publié: 2024
Sujets:
Accès en ligne:https://arxiv.org/abs/2407.10516
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866918007773593600
author Gallouët, Thomas O.
Natale, Andrea
Todeschi, Gabriele
author_facet Gallouët, Thomas O.
Natale, Andrea
Todeschi, Gabriele
contents In this article we study a variational problem providing a way to extend for all times minimizing geodesics connecting two given probability measures, in the Wasserstein space. This is simply obtained by allowing for negative coefficients in the classical variational characterization of Wasserstein barycenters. We show that this problem admits two equivalent convex formulations: the first can be seen as a particular instance of Toland duality and the second is a barycentric optimal transport problem. We propose an efficient numerical scheme to solve the latter formulation based on entropic regularization and a variant of Sinkhorn algorithm.
format Preprint
id arxiv_https___arxiv_org_abs_2407_10516
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Metric extrapolation in the Wasserstein space
Gallouët, Thomas O.
Natale, Andrea
Todeschi, Gabriele
Optimization and Control
In this article we study a variational problem providing a way to extend for all times minimizing geodesics connecting two given probability measures, in the Wasserstein space. This is simply obtained by allowing for negative coefficients in the classical variational characterization of Wasserstein barycenters. We show that this problem admits two equivalent convex formulations: the first can be seen as a particular instance of Toland duality and the second is a barycentric optimal transport problem. We propose an efficient numerical scheme to solve the latter formulation based on entropic regularization and a variant of Sinkhorn algorithm.
title Metric extrapolation in the Wasserstein space
topic Optimization and Control
url https://arxiv.org/abs/2407.10516