1 - Introduction
Published online by Cambridge University Press: 30 June 2022
Summary
This chapter discusses the fundamentally different mental images of large-dimensional machine learning (versus its small-dimensional counterpart), through the examples of sample covariance matrices and kernel matrices, on both synthetic and real data. Random matrix theory is presented as a flexible and powerful tool to assess, understand, and improve classical machine learning methods in this modern large-dimensional setting.
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- Random Matrix Methods for Machine Learning , pp. 1 - 34Publisher: Cambridge University PressPrint publication year: 2022