Random Matrix Methods for Machine Learning - Rilegato

Couillet, Romain; Liao, Zhenyu

Rilegato

ISBN 10: 1009123238 ISBN 13: 9781009123235

Casa editrice: Cambridge University Press, 2022

Riassunto

This unified random matrix approach to large-dimensional machine learning covers applications from power detection to deep neural networks.

Su questo libro

Informazioni sugli autori

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.

Dettagli dell?edizione

• Editore: Cambridge University Press
• Data di pubblicazione: 2022
• ISBN 10: 1009123238
• ISBN 13: 9781009123235
• Rilegatura: Copertina rigida
• Lingua: Inglese
• Numero di pagine: 408
• Contatto del produttore: non disponibile