Translator Disclaimer
2017 Basic models and questions in statistical network analysis
Miklós Z. Rácz, Sébastien Bubeck
Statist. Surv. 11(none): 1-47 (2017). DOI: 10.1214/17-SS117

Abstract

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.

Citation

Download Citation

Miklós Z. Rácz. Sébastien Bubeck. "Basic models and questions in statistical network analysis." Statist. Surv. 11 1 - 47, 2017. https://doi.org/10.1214/17-SS117

Information

Received: 1 September 2016; Published: 2017
First available in Project Euclid: 8 September 2017

zbMATH: 06790046
MathSciNet: MR3696007
Digital Object Identifier: 10.1214/17-SS117

Subjects:
Primary: 05C80, 60C05, 62-02

JOURNAL ARTICLE
47 PAGES


SHARE
Vol.11 • 2017
Back to Top