Venue: Microsoft Research Redmond
Building 99
14820 NE 36th St
Redmond, WA 98052
Contact: For event questions, please contact msrevent@microsoft.com
Deep learning is transforming the field of artificial intelligence, yet it is lacking solid theoretical underpinnings. This state of affair significantly hinders further progress, as exemplified by time-consuming hyperparameters optimization, or the extraordinary difficulties encountered in adversarial machine learning. Our three-day workshop stems on what we identify as the current main bottleneck: understanding the geometrical structure of deep neural networks. This problem is at the confluence of mathematics, computer science, and practical machine learning. We invite the leaders in these fields to bolster new collaborations and to look for new angles of attack on the mysteries of deep learning.
Keynotes
Peter Bartlett, University of California at Berkeley
Leon Bottou, Facebook
Anna Gilbert, University of Michigan
Piotr Indyk, MIT
S. T. Yau, Harvard
Invited Speakers
Emmanuel Abbe
Nina Balcan
Costis Daskalakis
Rong Ge
Suriya Gunasekar
Daniel Hsu
Yuanzhi Li
Tengyu Ma
Aleksander Madry
Andrea Montanari
Sasha Rakhlin
Mahdi Soltanolkotabi
Suvrit Sra
Nati Srebro
Soledad Villar
Program Committee members
Sébastien Bubeck
Ilya Razenshteyn
Adith Swaminathan
Greg Yang
Pengchuan Zhang