Mean-field approaches in Machine Learning and Statistics

Organizers

• Marc Hoffmann (University of Paris-Dauphine)
• Francis Bach (INRIA and Ecole Normale Superieure)

Description

The aim of this workshop is to gather specialists from machine learning and statistics to applied probability and analysis who share a common interest in mean-field models. Potential applications range from mean-field games to stochastic algorithms and simulations, neural networks and frequentist or Bayesian statistical inference for interacting systems.

Confirmed Speakers:

• Pierre Alquier (Center for Advanced Intelligence Project (AIP))
• Alberto Bietti (New York University)
• Joan Bruna (New York University)
• Lenaic Chizat (Centre National de la Recherche Scientifique (CNRS))
• Weinan E (Princeton University)
• Franca Hoffmann (University of Bonn)
• Florent Krzakala (EPFL (Ecole Polytechnique Fédérale de Lausanne))
• Song Mei (University of California, Berkeley (UC Berkeley))
• Patricia Reynaud-Bouret (CNRS Université Côte d’Azur)
• Johannes Schmidt-Hieber (University of Twente)
• Lenka Zdeborova (EPFL (Ecole Polytechnique Fédérale de Lausanne))