Mathematics of Machine Learning

April 14 – May 11, 2018

Organizers: Sebastian Bubeck (Microsoft Research), Luc Devroye (McGill), Gábor Lugosi (Pompeu Fabra)

The thematic activity focuses on mathematical challenges of machine learning. The spectacular success of machine learning in a wide range of applications opens many exciting theoretical challenges in a number of mathematical fields, including probability, statistics, combinatorics, optimization, and geometry. The CRM will bring together researchers of machine learning and mathematics to discuss these problems. The principal topics include combinatorial statistics, online learning, and deep neural networks.

The main activities include a workshop on “Combinatorial Statistics” and another one on “Modern Challenges in Learning Theory,” as well as regular seminars given by the invited researchers and scholars-in-residence.