High Dimensional Probability VII: The Cargese Volume (Hardcover)

ISBN 10: 3319405179 / ISBN 13: 9783319405179

Edité par Birkhauser, Basel, 2016

A propos de cet article

Hardcover. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

N° de réf. du vendeur 9783319405179

Détails bibliographiques

• Titre: High Dimensional Probability VII: The Cargese Volume (Hardcover)
• Éditeur: Birkhauser, Basel
• Date de parution: 2016
• Langue: anglais
• ISBN à 10 chiffres: 3319405179
• ISBN à 13 chiffres: 9783319405179
• Reliure: Hardcover
• Édition: Edition originale
• État de l'article: new

A propos de ce titre

Synopsis

This volume collects selected papers from the 7th High Dimensional Probability meeting held at the Institut d'Études Scientifiques de Cargèse (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 andperspectives to analyze random phenomena.