LIPIcs.FSTTCS.2020.1.pdf
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The Quest for Mathematical Understanding of Deep Learning (Invited Talk)
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40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2020)
Series: Leibniz International Proceedings in Informatics (LIPIcs)
Conference: IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS) - License:
Creative Commons Attribution 3.0 Unported license
- Publication Date: 2020-12-04
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Sanjeev Arora. The Quest for Mathematical Understanding of Deep Learning (Invited Talk). In 40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 182, p. 1:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
https://doi.org/10.4230/LIPIcs.FSTTCS.2020.1
https://doi.org/10.4230/LIPIcs.FSTTCS.2020.1
Abstract
Deep learning has transformed Machine Learning and Artificial Intelligence in the past decade. It raises fundamental questions for mathematics and theory of computer science, since it relies upon solving large-scale nonconvex problems via gradient descent and its variants. This talk will be an introduction to mathematical questions raised by deep learning, and some partial understanding obtained in recent years.
Subject Classification
ACM Subject Classification
- Theory of computation → Mathematical optimization
- Computing methodologies → Artificial intelligence
- Computing methodologies → Machine learning
Keywords
- machine learning
- artificial intelligence
- deep learning
- gradient descent
- optimization
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