E-book – High-Dimensional Statistics: A Non-Asymptotic Viewpoint (Cambridge Series in Statistical and Probabilistic Mathematics Book 48) 1st Edition, Kindle Edition (PDF Instant Download)
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ISBN-13: 978-1108571234
Author: Martin J. Wainwright
Recent years have witnessed an explosion in the volume and variety of data collected in all scientific disciplines and industrial settings. Such massive data sets present a number of challenges to researchers in statistics and machine learning. This book provides a self-contained introduction to the area of high-dimensional statistics, aimed at the first-year graduate level. It includes chapters that are focused on core methodology and theory – including tail bounds, concentration inequalities, uniform laws and empirical process, and random matrices – as well as chapters devoted to in-depth exploration of particular model classes – including sparse linear models, matrix models with rank constraints, graphical models, and various types of non-parametric models. With hundreds of worked examples and exercises, this text is intended both for courses and for self-study by graduate students and researchers in statistics, machine learning, and related fields who must understand, apply, and adapt modern statistical methods suited to large-scale data.
Please note: This is an Ebook, not a Paper Book or Audio Book!
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