High dimensional probability VII : the Cargése volume
Author(s)
Bibliographic Information
High dimensional probability VII : the Cargése volume
（Progress in probability / series editors, Thomas Liggett, Charles Newman, Loren Pitt, v. 71）
Birkhäuser , Springer, c2016
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Note
"The present volume is an outgrowth of the Seventh High Dimensional Probability Conference (HDP VII) held at the superb Institut d'Etudes Scientifiques de Cargése (IESC), France, May 26-30, 2014."--Preface
Includes bibliographical references
Other editors : Houdré, Christian. Mason, David M. Reynaud-Bouret, Patricia. Rosiński, Jan.
Description and Table of Contents
Description
This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'Etudes Scientifiques de Cargese (IESC) in Corsica, France.
High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions and limit theorems in infinite-dimensional spaces such as Hilbert spaces and Banach spaces. The most remarkable feature of this area is that it has resulted in the creation of powerful new tools and perspectives, whose range of application has led to interactions with other subfields of mathematics, statistics, and computer science. These include random matrices, nonparametric statistics, empirical processes, statistical learning theory, concentration of measure phenomena, strong and weak approximations, functional estimation, combinatorial optimization, and random graphs.
The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques and perspectives to analyze random phenomena.
Table of Contents
Dedication to Evarist Gine-Masdeu.- Inequalities and Convexity.- Limit Theorems.- Stochastic Processes.- High Dimensional Statistics.
by "Nielsen BookData"