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

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Ends
America/New_York