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Random Matrix Methods for Machine Learning
Engelsk Hardback
Random Matrix Methods for Machine Learning
Engelsk Hardback

863 kr
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Om denne bog
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.
Product detaljer
Sprog:
Engelsk
Sider:
408
ISBN-13:
9781009123235
Indbinding:
Hardback
Udgave:
ISBN-10:
1009123238
Kategori:
Udg. Dato:
21 jul 2022
Længde:
28mm
Bredde:
251mm
Højde:
177mm
Forlag:
Cambridge University Press
Oplagsdato:
21 jul 2022
Forfatter(e):
Kategori sammenhænge