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Table of contents (19 papers)
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Front Matter
Keywords
About this book
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.
Editors and Affiliations
Bibliographic Information
Book Title: High Dimensional Probability VIII
Book Subtitle: The Oaxaca Volume
Editors: Nathael Gozlan, Rafał Latała, Karim Lounici, Mokshay Madiman
Series Title: Progress in Probability
DOI: https://doi.org/10.1007/978-3-030-26391-1
Publisher: Birkhäuser Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-26390-4Published: 27 November 2019
Softcover ISBN: 978-3-030-26393-5Published: 27 November 2020
eBook ISBN: 978-3-030-26391-1Published: 26 November 2019
Series ISSN: 1050-6977
Series E-ISSN: 2297-0428
Edition Number: 1
Number of Pages: X, 458
Number of Illustrations: 1 b/w illustrations, 5 illustrations in colour