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On Learning Theory and Neural Networks

October 27, 2017 @ 11:00 am - 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

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.

 

Details

Date:
October 27, 2017
Time:
11:00 am - 12:00 pm
Event Category:

Venue

E18-304
50 Ames Street
Cambridge, MA 02139

Other

Speaker Name(s)
Amit Daniely (Google)
Bldg-Room #
E18-304