Optimization and Statistical Learning - OSL 2019

March 24, 2019 - March 29, 2019
This session focuses on recent advances in machine learning and mathematical optimization, with a special emphasis on their synergies with physical sciences. Both theoretical aspects and computational aspects in large-scale settings are of interest.
Session organized by:

Alexandre d’ASPREMONT, CNRS & DI ENS, Paris, France
Zaid HARCHAOUI, University of Washington, Seattle, USA
Julien MAIRAL, INRIA, Université Grenoble Alpes, France
Jérôme MALICK, CNRS, Université Grenoble Alpes, France
Philippe RIGOLLET, MIT, Cambridge, USA

For more information, please check the session's website.
Published on  October 26, 2018
Updated on  August 13, 2020