An opening colloquium about recent developments and challenges of high-dimensional statistical inference and machine learning. Speakers: Lenka Zdeborová (EPFL, Switzerland) and Andrea Montanari (Stanford, USA)
Thematic School: “Optimization & Algorithms”, featuring mini-courses on the study of high-dimensional (random) optimization landscapes, on the dynamics of optimization algorithms in high dimensions, on approximate message passing algorithms, and related topics.
List of speakers and subjects: here
Thematic School: “Models & Methods”, on tools and techniques for the analysis of high-dimensional models in statistical inference and machine learning, including tools from random matrix theory, statistical physics and spin glasses.
List of speakers and subjects: here.
Workshop: Recent developments beyond classical regimes in statistical learning
This workshop is focused on recent results on high-dimensional (supervised and unsupervised) machine learning and statistical inference. It will in particular involve a round-table debate with top experts on this domain about the major open problems on the field and some promising trends and recent developments.
Program, speakers and registration: please click here.
PhD students are funded (travel and accommodation) in some conditions, if they register as soon as possible and send a topic compliant CV.
Researchers can register during the month of June here.