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.

A mathematical introduction to deep learning, written by a group of leading experts in the field.

About the Author
Philipp Grohs is Professor of Applied Mathematics at the University of Vienna and Group Leader of Mathematical Data Science at the Austrian Academy of Sciences. Gitta Kutyniok is Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence at Ludwig-Maximilians Universitat Munchen and Adjunct Professor for Machine Learning at the University of Tromso.


Book Information
ISBN 9781316516782
Author Philipp Grohs
Format Hardback
Page Count 492
Imprint Cambridge University Press
Publisher Cambridge University Press
Weight(grams) 1070g
Dimensions(mm) 251mm * 174mm * 26mm