Bayesian estimation of the latent dimension and communities in stochastic blockmodels
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DOI: 10.1007/s11222-020-09946-6
Abstract: Spectral embedding of adjacency or Laplacian matrices of undirected graphs is a common technique for representing a network in a lower dimensional latent space, with optimal theoretical guarantees. The embedding can be used to estimate… read more here.
Keywords: dimension; latent dimension; estimation latent; bayesian estimation ... See more keywords
Estimation of the Number of Communities in the Stochastic Block Model
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DOI: 10.1109/tit.2020.3016331
Abstract: In this article we introduce an estimator for the number of communities in the Stochastic Block Model (SBM), based on the maximization of a penalized version of the so-called Krichevsky-Trofimov mixture distribution. We prove its… read more here.
Keywords: communities stochastic; number; block model; estimation number ... See more keywords