Mathematical Aspects of Learning Theory- 20 years later

Learning theory is one of the main research directions devoted to the study of the theory of data science. The focus of learning theory is on the nontrivial connections between all facets of information extraction and high dimensional phenomena; specifically on the way such phenomena are manifested in applications in statistics, optimization, and complexity theory.

By now it is understood that key questions in learning theory lead to deep problems in pure mathematics and in theoretical computer science. The goal of the proposed conference is to bring together researchers from all over the world who are interested in mathematical aspects of learning theory.

In 2004 CRM hosted a tremendously successful meeting on the mathematical foundations of learning theory. The key to success was to bring together leading mathematicians working in probability and high-dimensional geometry with researchers on theoretical machine learning. We hope to repeat the same formula 20 years later, after witnessing an explosion of the subject that nobody foresaw 20 years ago.

Liza Levina | University of Michigan

Gábor Lugosi | ICREA & Pompeu Fabra University

Shahar Mendelson | Australian National University

Roman Vershynin | UC Irvine

Emmanuel Abbe | École Polytechnique Fédérale de Lausanne
Morgane Austerne | Harvard University
Afonso Bandeira | ETH Zürich
Sebastien Bubeck | Microsoft Research
Emmanuel Candès | Stanford University
Nicolò Cesa-Bianchi | University of Milan
Luc Devroye | McGill University
Jian Ding | Peking University
Ronen Eldan | Microsoft Research
Christophe Giraud | Institut de Mathématiques d’Orsay
Olga Klopp | ESSEC Business School
Vladimir Koltchinskii | Georgia Institute of Technology
Shay Moran | Technion – Israel Institute of Technology
Jelani Nelson | UC Berkeley
Gergely Neu | Universitat Pompeu Fabra
Alexander Rakhlin | MIT
Tselil Schramm | Stanford University
Daniel Spielman | Yale University
Suvrit Sra | MIT
Alexandre Tsybakov | CREST-ENSAE Institut Polytechnique de Paris 
Martin Wainwright | MIT
Amir Yehudayoff | Technion – Israel Institute of Technology | University of Copenhagen
Nikita Zhivotovskiy | UC Berkeley
Piotr Zwiernik | University of Toronto

Applications closed

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