Practically Relevant Theory and Theoretically Relevant Practice of Deep Learning

Tuesday, May 17, 2016 - 2:00pm - 2:50pm
Keller 3-180
Shai Shalev-Shwartz (Hebrew University)
I will describe two contradicting lines of work. On one hand, a practical work on autonomous driving I was doing at Mobileye, in which deep learning is one of the key ingredients. On the other hand, theoretical work I was doing at the Hebrew university showing strong hardness of learning results. Bridging this gap is a great challenge. I will describe some approaches toward a solution, focusing on practically relevant theory and theoretically relevant practice.
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