Random Matrix Methods for Machine Learning - Hardcover

Couillet, Romain; Liao, Zhenyu

Hardcover

ISBN 10: 1009123238 ISBN 13: 9781009123235

Verlag: Cambridge University Press, 2022

Inhaltsangabe

This book presents a unified theory of random matrices for applications in machine learning, offering a large-dimensional data vision that exploits concentration and universality phenomena. This enables a precise understanding, and possible improvements, of the core mechanisms at play in real-world machine learning algorithms. The book opens with a thorough introduction to the theoretical basics of random matrices, which serves as a support to a wide scope of applications ranging from SVMs, through semi-supervised learning, unsupervised spectral clustering, and graph methods, to neural networks and deep learning. For each application, the authors discuss small- versus large-dimensional intuitions of the problem, followed by a systematic random matrix analysis of the resulting performance and possible improvements. All concepts, applications, and variations are illustrated numerically on synthetic as well as real-world data, with MATLAB and Python code provided on the accompanying website.

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Über die Autorinnen und Autoren

Romain Couillet is a Full Professor at Grenoble-Alpes University, France. Prior to that, he was a Full Professor at CentraleSupélec, University of Paris-Saclay. His research topics are in random matrix theory applied to statistics, machine learning, and signal processing. He is the recipient of the 2021 IEEE/SEE Glavieux prize, of the 2013 CNRS Bronze Medal, and of the 2013 IEEE ComSoc Outstanding Young Researcher Award.

Zhenyu Liao is an Associated Professor with Huazhong University of Science and Technology (HUST), China. He is the recipient of the 2021 East Lake Youth Talent Program Fellowship of HUST, the 2019 ED STIC Ph.D. Student Award, and the 2016 Supélec Foundation Ph.D. Fellowship of University of Paris-Saclay, France.

Details zur Ausgabe

• Verlag: Cambridge University Press
• Erscheinungsdatum: 2022
• Sprache: Englisch
• ISBN 10: 1009123238
• ISBN 13: 9781009123235
• Einband: Tapa dura
• Anzahl der Seiten: 412
• Kontakt zum Hersteller: Nicht verfügbar
• Verantwortliche Person: Avery; https://www.avery.fr/; ; chemin des peupliers 27; Dardilly; Frankreich