[Todos CMAT] SEMINARIO DE PROBABILIDAD Y ESTADÍSTICA - RECORDATORIO

[seminarios en cmat.edu.uy]

SEMINARIO DE PROBABILIDAD Y ESTADÍSTICA

Viernes 15 de junio, de 12:00 PM a 01:00 PM, Salón de Seminarios. Centro de Matemática



Expositor: Marco Cuturi, CREST - ENSAE , Université Paris-Saclay

Título: Optimal transport in data-sciences: why and how.

Resumen: The interest for optimal transport theory in the fields of data science, machine learning and statistics has grown tremendously in recent years. This talk will first discuss why that theory, which provides an intuitive and geometric perspective to compare probability distributions, is a natural alternative to more classical information divergences such as the Kullback-Leibler geometry. I will then show how some computational and statistical challenges posed by the original formulations of optimal transport, dating back to Monge (1782) and Kantorovich (1942), can be addressed using regularization. I will finally conclude by showcasing the scalability of novel new statistical methods built upon optimal transport, with varied applications in imaging, signal / natural language processing and image tagging.

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Véalo aquí: http://www.cmat.edu.uy/events/seminarios