Variational Bayesian inference and complexity control for stochastic block models

• Published in: Statistical modelling Vol. 12; no. 1; pp. 93 - 115
• Main Authors: Latouche, P, Birmelé, E, Ambroise, C
• Format: Journal Article
• Language: English
• Published: New Delhi, India SAGE Publications 01.02.2012; Sage Publications Ltd
• Subjects: Algorithms; Applications; Approximation; Cluster analysis; Clustering; Methodology; Optimization techniques; Social sciences; Software; Statistics; Stochastic models; Studies; variational Bayes EM; integrated observed-data likelihood; integrated complete-data likelihood; variational EM; random graphs; stochastic block models; community detection

It is now widely accepted that knowledge can be acquired from networks by clustering their vertices according to the connection profiles. Many methods have been proposed and in this paper we concentrate on the Stochastic Block Model (SBM). The clustering of vertices and the estimation of SBM model p...