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High-Dimension al Statistics Non-Asymptotic Viewpoint 48 Martin J.… 9781108498029
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- Come Nuovo
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- ISBN
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Product Information
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.
Product Identifiers
Publisher
Cambridge University Press
ISBN-13
9781108498029
eBay Product ID (ePID)
9046633845
Product Key Features
Number of Pages
568 Pages
Publication Name
High-Dimensional Statistics: a Non-Asymptotic Viewpoint
Language
English
Subject
Economics, Computer Science, Biology, Mathematics
Publication Year
2019
Type
Textbook
Subject Area
Data Analysis
Series
Cambridge Series in Statistical and Probabilistic Mathematics
Format
Hardcover
Dimensions
Item Height
260 mm
Item Weight
1200 g
Item Width
183 mm
Additional Product Features
Country/Region of Manufacture
United Kingdom
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