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Basic models and questions in statistical network analysis

Author(s): Rácz, Miklos Z; Bubeck, S

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Abstract: © 2017, Institute of Mathematical Statistics. All rights reserved. Extracting information from large graphs has become an important statistical problem since network data is now common in various fields. In this minicourse we will investigate the most natural statistical questions for three canonical probabilistic models of networks: (i) community detection in the stochastic block model, (ii) finding the embedding of a random geometric graph, and (iii) finding the original vertex in a preferential attachment tree. Along the way we will cover many interesting topics in probability theory such as Pólya urns, large deviation theory, concentration of measure in high dimension, entropic central limit theorems, and more.
Publication Date: 1-Jan-2017
Citation: Rácz, MZ, Bubeck, S. (2017). Basic models and questions in statistical network analysis. Statistics Surveys, 11 (1 - 47. doi:10.1214/17-SS117
DOI: doi:10.1214/17-SS117
EISSN: 1935-7516
Pages: 1 - 47
Type of Material: Journal Article
Journal/Proceeding Title: Statistics Surveys
Version: Author's manuscript

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