Simons Collaboration on Mathematical and Scientific Foundations
of Deep Learning Annual Meeting: September 30-October 1, 2021
Simons Foundation
Gerald D. Fischbach Auditorium, 2nd Floor
160 Fifth Avenue at 21st Street
New York, NY 10010
Organizers:
Peter Bartlett, University of California, Berkeley
Rene Vidal, Johns Hopkins University
Meeting Goals:
This meeting will bring together members of the NSF-Simons Research Collaborations on the Mathematical and Scientific Foundations of Deep Learning (MoDL), which are aimed at developing mathematical and statistical tools to understand the success and limitations of deep learning, to guide the design of more effective methods, and to initiate the study of the mathematical problems that emerge. The meeting aims to report on progress in these directions in the first year and to stimulate discussions of future directions in the collaborations.
Speakers:
Andrea Montanari, Stanford University
Nati Srebro, Toyota Technological Institute at Chicago
Peter Bartlett, University of California, Berkeley
Gil Kur, Massachusetts Institute of Technology
Emmanuel Candès, Stanford University
René Vidal and Soledad Villar, Johns Hopkins University
Alejandro Ribeiro, University of Pennsylvania
Yi Ma, University of California, Berkeley
