High Dimensional Probability VIII : The Oaxaca Volume

Nathael Gozlan

ISBN 10: 3030263908 / ISBN 13: 9783030263904

Published by Springer International Publishing, 2019

About this Item

Druck auf Anfrage Neuware - Printed after ordering - This volume collects selected papers from the 8th High Dimensional Probability meeting held at Casa Matemática Oaxaca (CMO), Mexico. 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, random graphs, information theory and convex geometry. The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques and perspectives to analyze random phenomena.

Seller Inventory # 9783030263904

Bibliographic Details

• Title: High Dimensional Probability VIII : The Oaxaca Volume
• Publisher: Springer International Publishing
• Publication Date: 2019
• Language: English
• ISBN 10: 3030263908
• ISBN 13: 9783030263904
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 31D millimeters 241 millimeters width by 160 millimeters height by 31 millimeters depth
• Weight: 863 grams

About this title

Synopsis

This volume collects selected papers from the 8th High Dimensional Probability meeting held at Casa Matemática Oaxaca (CMO), Mexico.

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, random graphs, information theory and convex geometry.

The contributions in this volume show that HDP theory continues to thrive and develop new tools, methods, techniques and perspectives to analyze random phenomena.