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Title: A quick overview of deep learning theory: part 1
By: Sébastien Gerchinovitz, IMT
Abstract: The recent successful practical results in deep learning have triggered a renewed interest in deep learning theory. In this talk we will briefly review old and new results about approximation theory and statistical complexity for feed-forward neural networks.
Location: UPS amphi 1R3-Schwartz
Note: These introductory lectures, organized by IMT and the AOC group, are directed to an audience of deep learning beginners *with an already solid mathematical background*.
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