| 000 -LEADER |
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| fixed length control field |
a |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
231101b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781108498029 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
519.5 |
| Item number |
WAI |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Wainwright, Martin J. |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
High-dimensional statistics : a non-asymptotic viewpoint |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc |
Cambridge University Press, |
| Date of publication, distribution, etc |
2019 |
| Place of publication, distribution, etc |
Cambridge : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xvii, 552 p. ; |
| Other physical details |
ill., |
| Dimensions |
26 cm. |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
64.99 |
| Price type code |
GBP |
| Unit of pricing |
107.60 |
| 490 ## - SERIES STATEMENT |
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| Series statement |
Cambridge series in statistical and probabilistic mathematics |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references and indexes. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
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. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Big data |
|
|---|
| Topical term or geographic name as entry element |
Mathematical statistics |
|
|---|
| Topical term or geographic name as entry element |
Metric entropy |
|
|---|
| Topical term or geographic name as entry element |
Frobenius norm |
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| Topical term or geographic name as entry element |
Hilbert space |
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| Topical term or geographic name as entry element |
Kullback–Leibler divergence |
|
|---|
| Topical term or geographic name as entry element |
Lipschitz functions |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Books |