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High dimensional probability VIIthe ...

(1998 :)

High dimensional probability VIIthe Cargese Volume /

Record Type:	Electronic resources : Monograph/item
Title/Author:	High dimensional probability VIIedited by Christian Houdre ... [et al.].
Reminder of title:	the Cargese Volume /
remainder title:	High dimensional probability 7
other author:	Houdre, Christian.
corporate name:
Published:	Cham :Springer International Publishing :2016.
Description:	xxviii, 461 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Probabilities
Online resource:	http://dx.doi.org/10.1007/978-3-319-40519-3
ISBN:	9783319405193$q(electronic bk.)

High dimensional probability VIIthe Cargese Volume /
High dimensional probability VIIthe Cargese Volume /[electronic resource] :High dimensional probability 7edited by Christian Houdre ... [et al.]. - Cham :Springer International Publishing :2016. - xxviii, 461 p. :ill., digital ;24 cm. - Progress in probability,v.711050-6977 ;. - Progress in probability ;43..

Dedication to Evarist Gine-Masdeu -- Inequalities and Convexity -- Limit Theorems -- Stochastic Processes -- High Dimensional Statistics.

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.

ISBN: 9783319405193$q(electronic bk.)

Standard No.: 10.1007/978-3-319-40519-3doiSubjects--Topical Terms:

269300
Probabilities

LC Class. No.: QA273.A1

Dewey Class. No.: 519.2

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490 1 $a Progress in probability, $x 1050-6977 ; $v v.71
505 0 $a Dedication to Evarist Gine-Masdeu -- Inequalities and Convexity -- Limit Theorems -- Stochastic Processes -- High Dimensional Statistics.
520 $a 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.
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