Random Matrix Methods for Machine Learning
by Romain Couillet, Zhenyu Liao
Random Matrix Methods for Machine Learning presents a focused exploration of random matrix methods as they relate to machine learning. Written by Romain Couillet and Zhenyu Liao, the book connects mathematical analysis with a central area of contemporary computer science.
About This Book
Random Matrix Methods for Machine Learning explores the relationship between random matrix methods and machine learning.
The book is authored by Romain Couillet and Zhenyu Liao.
Its subject sits at the intersection of mathematical methods, computational theory, and machine learning.
This title may serve readers seeking a focused treatment of random matrix techniques within a machine learning context.
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