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Computational Optimal Transport

The theory of Optimal Transport (OT) dates back to the French mathematician, physician and chemist G. Monge (1746 - 1818) and has been (re)discovered in many settings and under di erent forms, giving it a rich history. While Monge's seminal work was motivated by an engineering problem, Tolstoi in the 1920s and Hitchcock, Kantorovich and Koopmans in the 1940s established its signi cance to logistics and economics. Dantzig solved it numerically in 1949 within the framework of linear programming, giving OT a rm footing in optimization. OT was later revisited by analysts in the 1990s, notably Brenier, while also gaining fame in computer vision under the name of earth mover's distances. Recent years have witnessed yet another revolution in the spread of OT, thanks to the emergence of approximate solvers that can scale to large problem dimensions. As a consequence, OT is being increasingly used to unlock various problems in imaging sciences (such as color or texture processing), graphics (for shape manipulation) or machine learning (for regression, classi cation and generative modeling).

The goal of the seminar is to get an overview of the main theoretical aspects of OT, to show how to turn these insights into fast computational schemes and to address various applications.

Ablauf: 45-minütige Vorträge mit anschließender Diskussion, eventuell nicht geblockt.

Anmeldung: Über ISIS bis Do. 16.04.2020


  • Vorbesprechung: Fr 24.04.2020   um   12:00 Uhr

  • Vorträge: werden wegen der derzeitigen Notsituation in der ersten Veranstaltung abgesprochen. Bisherige Termine waren:

    Freitag 5.6.2020 von 10:00 - 16:00 Uhr
    Freitag 12.6.2020 von 10:00 - 16:00 Uhr
    Samstag 13.6.2020 von 8:00 - 14:00 Uhr

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