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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.