On Learning Theory and Neural Networks

Friday, October 27, 2017 - 11:00am to Saturday, October 28, 2017 - 10:55am

Event Calendar Category

IDSS

Speaker Name

Amit Daniely

Affiliation

Google

Building and Room number

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

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.