JdS2012


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Résumé 202 :

Consistency of maximum-likelihood and variational estimators in the Stochastic Block Model
CELISSE, Alain ; Daudin, Jean-Jacques ; PIERRE, Laurent
UMR 8524 CNRS - Lille 1, MODAL

The \textit{stochastic block model} (SBM) is a probabilistic model designed to describe heterogeneous \textit{directed} and \textit{undirected} graphs. % In this paper, we address the asymptotic inference on SBM by use of maximum-likelihood and variational approaches. % The identifiability of SBM is proved, while asymptotic properties of maximum-likelihood and variational estimators are provided. In particular, the consistency of these estimators is settled, which is, to the best of our knowledge, the first result of this type for variational estimators with random graphs.