High-dimensional statistics : a non-asymptotic viewpoint /
Martin J. Wainwright.
Bok Engelsk 2019 Martin Wainwright,· Electronic books.
| Omfang | 1 online resource (xvii, 552 pages) : : digital, PDF file(s).
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| Utgave | 1st ed.
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| Opplysninger | Title from publisher's bibliographic system (viewed on 13 Feb 2019).. - 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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| Emner | |
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| Dewey | |
| ISBN | 1-108-57282-0
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