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Large Deviations for Random Graphs : École d'Été de Probabilités de Saint-Flour XLV - 2015

Large Deviations for Random Graphs : École d'Été de Probabilités de Saint-Flour XLV - 2015

Large Deviations for Random Graphs : École d'Été de Probabilités de Saint-Flour XLV - 2015 Paperback - 2017

by Sourav Chatterjee

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Paperback. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; 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, probabi
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  • Title Large Deviations for Random Graphs : École d'Été de Probabilités de Saint-Flour XLV - 2015
  • Author Sourav Chatterjee
  • Binding Paperback
  • Condition New
  • Publisher Springer
  • Publication date 2017
  • Features Illustrated
  • Bookseller's Inventory # ria9783319658155_inp
  • ISBN 9783319658155
  • Quantity available 211

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Reader reviews for Large Deviations for Random Graphs : École d'Été de Probabilités de Saint-Flour XLV - 2015

From the publisher

First book-length treatment of large deviations for random graphs, plus a chapter on exponential random graphs

Contains a summary of important results from graph limit theory with complete proofs

Written in a style for beginning graduate students, self-contained with essentially no need for background knowledge other than some amount of graduate probability and analysis

From the rear cover

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.
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