PhD Defense: The First Principles of Deep Learning and Compression
Max Ehrlich
Abstract
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Bio
Max Ehrlich is a Ph.D. candidate in the Computer Science department. His research studies ways to improve classical compression using deep learning with a special focus on methods that are motivated by the underlying engineering decisions of the compression algorithms.
This talk is organized by Tom Hurst