Random Matrix Methods for Machine Learning (e-bog) af Liao, Zhenyu
Liao, Zhenyu (forfatter)

Random Matrix Methods for Machine Learning e-bog

619,55 DKK (inkl. moms 774,44 DKK)
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 basic...
E-bog 619,55 DKK
Forfattere Liao, Zhenyu (forfatter)
Udgivet 28 juli 2022
Genrer Probability and statistics
Sprog English
Format pdf
Beskyttelse LCP
ISBN 9781009301893
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.