Mathematical aspects of deep learning / edited by Philipp Grohs, Gitta Kutyniok.

Format
Book
Language
English
Published/​Created
Cambridge : Cambridge University Press, 2023.
Description
1 online resource (xviii, 473 pages) : digital, PDF file(s).

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Editor
Summary note
In recent years the development of new classification and regression algorithms based on deep learning has led to a revolution in the fields of artificial intelligence, machine learning, and data analysis. The development of a theoretical foundation to guarantee the success of these algorithms constitutes one of the most active and exciting research topics in applied mathematics. This book presents the current mathematical understanding of deep learning methods from the point of view of the leading experts in the field. It serves both as a starting point for researchers and graduate students in computer science, mathematics, and statistics trying to get into the field and as an invaluable reference for future research.
Notes
Title from publisher's bibliographic system (viewed on 30 Nov 2022).
ISBN
9781009025096 (ebook)
Statement on language in description
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