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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
High-Dimensional Statistics: A Non-Asymptotic Viewpoint

High-Dimensional Statistics: A Non-Asymptotic Viewpoint

Wainwright, Martin J.

Hardcover

Series: Cambridge Statistical and Probabilistic Mathematics, Book 48

Probability & Statistics

ISBN10: 1108498027
ISBN13: 9781108498029
Publisher: Cambridge University Press
Published: Feb 21 2019
Pages: 568
Weight: 3.00
Height: 1.70 Width: 7.30 Depth: 10.10
Language: English
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.

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