%0 Book
%0 [E-Book] /
%A Wainwright, Martin
%I Cambridge University Press
%D 2019
%C Cambridge
%P 1 online resource (xvii, 552 pages)
%G englisch
%B Cambridge series in statistical and probabilistic mathematics ;
%V 48
%@ 9781108498029
%@ 9781108627771
%T High-dimensional statistics : a non-asymptotic viewpoint [E-Book]
%U https://www.cambridge.org/core/product/identifier/9781108627771/type/BOOK
%X 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.
%K Mathematical statistics
%K Big data.
%~ JuLib eXtended
%W Forschungszentrum Jülich GmbH, Zentralbibliothek