Matrices, Statistics and Big Data

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This volume features selected, refereed papers on various aspects of statistics, matrix theory and its applications to statistics, as well as related numerical

Mathematics of Big Data

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The first book to present the common mathematical foundations of big data analysis across a range of applications and technologies. Today, the volume, velocity,

Spectral Analysis of Large Dimensional Random Matrices

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The aim of the book is to introduce basic concepts, main results, and widely applied mathematical tools in the spectral analysis of large dimensional random mat

Foundations of Data Science

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This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and a

Large Sample Covariance Matrices and High-Dimensional Data Analysis

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High-dimensional data appear in many fields, and their analysis has become increasingly important in modern statistics. However, it has long been observed that