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Random Matrix Methods for Machine Learning - Couillet, Romain, and Liao, Zhenyu
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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, ...

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Random Matrix Methods for Machine Learning 2022, Cambridge University Press, Cambridge

ISBN-13: 9781009123235

Hardcover