Date de l'événement : le 19 janvier 2018
Centre de Conférences Marilyn et James Simons, Bures-sur-Yvette
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The aim of the workshop "Statistics/Learning at Paris-Saclay" is to bring together mathematicians and computer scientists around some talks on recent results in statistics and machine learning. It will take place on January 19h 2018 at Bures-sur-Yvette.

Various theoretical topics in machine learning, statistics and probability theory will be presented as well as applications to social and ecological networks and brain mapping.

Organised by : Pierre Alquier et Guillaume Charpiat, with support from : GT Deep Net & GT Pasadena

Invited speakers :

  • Romain Couillet (Centrale-Supéléc)
  • Marco Cuturi (ENSAE ParisTech)
  • Sophie Donnet (INRA)
  • Anna Korba (Telecom ParisTech)
  • James Ridgway (Agro ParisTech)
  • Bertrand Thirion (INRIA)

The presentations will be in French, with slides (and potentially questions) in English.

On the programme:

  • A random matrix approach to bigdata machine learning, Romain Couillet (Centrale-Supéléc)
  • Generative Models and Optimal Transport, Marco Cuturi (ENSAE ParisTech)
  • Introduction aux modèles à blocs stochastiques pour la modélisation de réseaux sociaux et écologiques, Sophie Donnet (INRA)
  • Concentration of tempered posteriors and of their variational approximations, James Ridgway (Agro ParisTech)
  • Toward a rigorous statistical framework for functional brain mapping, Bertrand Thirion (INRIA)
  • Ranking median regression: Learning to order through local consensus, Anna Korba (Telecom ParisTech)

Registration and more information online