High-Dimensional Statistics A Non-Asymptotic Viewpoint

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  • Engels
  • Hardcover
  • 9781108498029
  • 21 februari 2019
  • 568 pagina's
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Samenvatting

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.

Productspecificaties

Inhoud

Taal
en
Bindwijze
Hardcover
Oorspronkelijke releasedatum
21 februari 2019
Aantal pagina's
568
Illustraties
Nee

Betrokkenen

Hoofdauteur
Martin J. Wainwright
Hoofduitgeverij
Cambridge University Press

Overige kenmerken

Extra groot lettertype
Nee
Product breedte
183 mm
Product hoogte
35 mm
Product lengte
260 mm
Studieboek
Ja
Verpakking breedte
183 mm
Verpakking hoogte
35 mm
Verpakking lengte
260 mm
Verpakkingsgewicht
1200 g

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EAN
9781108498029
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