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Stochastics and Statistics Seminar

On Learning Theory and Neural Networks

October 27, 2017 @ 11:00 am - 12:00 pm

Amit Daniely (Google)


Abstract:  Can learning theory, as we know it today, form a theoretical basis for neural networks. I will try to discuss this question in light of two new results — one positive and one negative.

Based on joint work with Roy Frostig, Vineet Gupta and Yoram Singer, and with Vitaly Feldman

Biography: Amit Daniely is an Assistant Professor at the Hebrew University in Jerusalem, and a research scientist at Google Research, Tel-Aviv. Prior to that, he was a research scientist at Google Research, Mountain-View. Even prior to that, he was a Ph.D. student at the Hebrew University of Jerusalem, Israel, supervised by Nati Linial and Shai Shalev-Shwartz. His main research interest is Machine Learning Theory.


MIT Statistics + Data Science Center
Massachusetts Institute of Technology
77 Massachusetts Avenue
Cambridge, MA 02139-4307