[isabelle] New in the AFP: Deep Learning
We have a new entry, on the subject of machine learning. Itâs quite a big development, and available to download here: https://www.isa-afp.org/entries/Deep_Learning.shtml
Expressiveness of Deep Learning
Author: Alexander Bentkamp (bentkamp at gmail.com)
Contributors: Florian Haftmann, Andreas Lochbihler
Abstract: Deep learning has had a profound impact on computer science in recent years, with applications to search engines, image recognition and language processing, bioinformatics, and more. Recently, Cohen et al. provided theoretical evidence for the superiority of deep learning over shallow learning. This formalization of their work simplifies and generalizes the original proof, while working around the limitations of the Isabelle type system. To support the formalization, I developed reusable libraries of formalized mathematics, including results about the matrix rank, the Lebesgue measure, and multivariate polynomials, as well as a library for tensor analysis.
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