On Learning Theory and Neural Networks

On October 27, 2017 at 11:00 am till 12:00 pm
Amit Daniely (Google)
E18-304

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

BiographyAmit 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.