Random Matrix Methods for Machine Learning
Couillet, Romain/ Liao, Zhenyu
ISBN 10: 1009123238 ISBN 13: 9781009123235
Published by Cambridge University Press, 2022
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Hardcover
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About this Item
Description:
450 pages. 9.96x6.97x0.91 inches. In Stock. This item is printed on demand. Seller Inventory # __1009123238
Synopsis:
This unified random matrix approach to large-dimensional machine learning covers applications from power detection to deep neural networks.
About the Authors:
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.
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Bibliographic Details
Title: Random Matrix Methods for Machine Learning
Publisher: Cambridge University Press
Publication Date: 2022
Binding: Hardcover
Condition: Brand New