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Random Matrix Methods for Machine Learning

Random Matrix Methods for Machine Learning

918 kr

918 kr

I lager

Tis, 29 jul - mån, 4 aug


Säker betalning

14-dagars öppet köp


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Adlibris

Produktbeskrivning

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.

Artikel.nr.

beef048f-b1e4-56b0-888a-1deb9a59f8e7

Random Matrix Methods for Machine Learning

918 kr

918 kr

I lager

Tis, 29 jul - mån, 4 aug


Säker betalning

14-dagars öppet köp


Säljs och levereras av

Adlibris