High Dimensional Probability VIII / Progress in Probability Bd.74 (PDF)
High Dimensional Probability (HDP) is an area of mathematics that includes the study of probability distributions...
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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.
- 2019, 1st ed. 2019, 458 Seiten, Englisch
- Herausgegeben: Nathael Gozlan, Rafal Latala, Karim Lounici, Mokshay Madiman
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3030263916
- ISBN-13: 9783030263911
- Erscheinungsdatum: 26.11.2019
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- Größe: 4.88 MB
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