Random Matrix Methods for Machine Learning

Random Matrix Methods for Machine Learning
Author :
Publisher : Cambridge University Press
Total Pages : 411
Release :
ISBN-10 : 9781009123235
ISBN-13 : 1009123238
Rating : 4/5 (238 Downloads)

Book Synopsis Random Matrix Methods for Machine Learning by : Romain Couillet

Download or read book Random Matrix Methods for Machine Learning written by Romain Couillet and published by Cambridge University Press. This book was released on 2022-07-21 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unified random matrix approach to large-dimensional machine learning covers applications from power detection to deep neural networks.


Random Matrix Methods for Machine Learning Related Books

Random Matrix Methods for Machine Learning
Language: en
Pages: 411
Authors: Romain Couillet
Categories: Computers
Type: BOOK - Published: 2022-07-21 - Publisher: Cambridge University Press

GET EBOOK

This unified random matrix approach to large-dimensional machine learning covers applications from power detection to deep neural networks.
Random Matrix Methods for Machine Learning
Language: en
Pages: 412
Authors: Romain Couillet
Categories: Computers
Type: BOOK - Published: 2022-07-21 - Publisher: Cambridge University Press

GET EBOOK

This book presents a unified theory of random matrices for applications in machine learning, offering a large-dimensional data vision that exploits concentratio
A First Course in Random Matrix Theory
Language: en
Pages: 371
Authors: Marc Potters
Categories: Computers
Type: BOOK - Published: 2020-12-03 - Publisher: Cambridge University Press

GET EBOOK

An intuitive, up-to-date introduction to random matrix theory and free calculus, with real world illustrations and Big Data applications.
Matrix Methods in Data Mining and Pattern Recognition
Language: en
Pages: 226
Authors: Lars Elden
Categories: Computers
Type: BOOK - Published: 2007-07-12 - Publisher: SIAM

GET EBOOK

Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented b
An Introduction to Matrix Concentration Inequalities
Language: en
Pages: 230
Authors: Joel Aaron Tropp
Categories: Matrix derivatives
Type: BOOK - Published: 2015 - Publisher:

GET EBOOK

Random matrices now play a role in many areas of theoretical, applied, and computational mathematics. Therefore, it is desirable to have tools for studying rand