A large deviation approach to optimal transport
| dc.creator | Léonard, Christian | |
| dc.date | 2007-10-08 | |
| dc.date.accessioned | 2026-07-07T08:34:41Z | |
| dc.date.available | 2026-07-07T08:34:41Z | |
| dc.description | A probabilistic method for solving the Monge-Kantorovich mass transport problem on $R^d$ is introduced. A system of empirical measures of independent particles is built in such a way that it obeys a doubly indexed large deviation principle with an optimal transport cost as its rate function. As a consequence, new approximation results for the optimal cost function and the optimal transport plans are derived. They follow from the Gamma-convergence of a sequence of normalized relative entropies toward the optimal transport cost. A wide class of cost functions including the standard power cost functions $|x-y|^p$ enter this framework. | |
| dc.identifier | https://arxiv.org/abs/0710.1461 | |
| dc.identifier | http://arxiv.org/abs/0710.1461 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/139524 | |
| dc.subject | Probability | |
| dc.subject | Optimization and Control | |
| dc.subject | 49J45, 49J53, 58E99, 60F10, 60G57, 90B06 | |
| dc.title | A large deviation approach to optimal transport | |
| dc.type | text |