Thematic program with short courses, seminars and workshops

In learning and modern statistics, it is usually assumed that although data is observed in very high dimension, it actually live on — or near — a geometric structure of low dimension. The knowledge of such a low-complexity structure is of fundamental importance so as to improve both theoretical and computational aspects of a learning procedures.

This workshop is part of a series of events throughout the fall: IHP Geometry and Statistics in Data Sciences which will include courses that will be posted online soon.

Invited Speakers

Peter Bartlett (UC Berkeley)
Mikhail Belkin (UC San Diego)
Clément Bérenfeld (CEREMADE, Dauphine)
Gilles Blanchard (LMO, Orsay)
Alexandra Carpentier (Potsdam)
Alexander Cloninger (UC San Diego)
Didong Li (Princeton)
Adeline Fermanian (Mines ParisTech)
John Harlim (Penn State)
Christian Hennig (Bologna)
Claire Lacour (Paris-Est, Marne-la-Vallée)
Sophie Langer (TU Darmstadt)
Marina Meila (University of Washington)
Alessandro Rinaldo (Carnegie Mellon)
Judith Rousseau (Oxford)
Botond Szabó (Bocconi)
Johannes Schmidt-Hieber (Twente)
Vasiliki Velona (Hebrew University of Jerusalem)
Nicolas Verzelen (Inrae Montpellier)

Organizers: Eddie Aamari (LPSM, CNRS), Catherine Aaron (LMBP, Université Clermont Auvergne) Frédéric Chazal (LMO, INRIA), Aurélie Fischer (LPSM, Université de Paris) Marc Hoffmann (CEREMADE, Paris Dauphine), Alice Le Brigant (SAMM, Paris 1 Panthéon Sorbonne) Clément Levrard (LPSM, Université de Paris), Bertrand Michel (LMJL, Ecole Centrale Nantes)