
Large Deviations for Random Graphs
École d'Été de Probabilités de Saint-Flour XLV - 2015
Sourav Chatterjee(Author)
Springer (Publisher)
Published on 2. September 2017
Book
Paperback/Softback
XI, 170 pages
978-3-319-65815-5 (ISBN)
Description
This book addresses the emerging body of literature on the study of rare events in random graphs and networks. For example, what does a random graph look like if by chance it has far more triangles than expected? Until recently, probability theory offered no tools to help answer such questions. Important advances have been made in the last few years, employing tools from the newly developed theory of graph limits. This work represents the first book-length treatment of this area, while also exploring the related area of exponential random graphs. All required results from analysis, combinatorics, graph theory and classical large deviations theory are developed from scratch, making the text self-contained and doing away with the need to look up external references. Further, the book is written in a format and style that are accessible for beginning graduate students in mathematics and statistics.
Reviews / Votes
"This nice book is recommended to all probabilists who wish to study the beautiful theory of large deviations for random graphs." (Zakhar Kabluchko, Mathematical Reviews, April, 2018)More details
Series
Edition
1st ed. 2017
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Illustrations
XI, 170 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 11 mm
Weight
289 gr
ISBN-13
978-3-319-65815-5 (9783319658155)
DOI
10.1007/978-3-319-65816-2
Schweitzer Classification
Other editions
Additional editions

Sourav Chatterjee
Large Deviations for Random Graphs
École d'Été de Probabilités de Saint-Flour XLV - 2015
E-Book
08/2017
Springer
€85.59
Available for download
Content
1. Introduction.- 2. Preparation.- 3. Basics of graph limit theory.- 4. Large deviation preliminaries.- 5. Large deviations for dense random graphs.- 6. Applications of dense graph large deviations.- 7. Exponential random graph models.- 8. Large deviations for sparse graphs.- Index.