A Tractable Fully Bayesian Method for the Stochastic Block Model

@article{Hayashi2016ATF,
  title={A Tractable Fully Bayesian Method for the Stochastic Block Model},
  author={Kohei Hayashi and Takuya Konishi and Tatsuro Kawamoto},
  journal={CoRR},
  year={2016},
  volume={abs/1602.02256}
}
The stochastic block model (SBM) is a generative model revealing macroscopic structures in graphs. Bayesian methods are used for (i) cluster assignment inference and (ii) model selection for the number of clusters. In this paper, we study the behavior of Bayesian inference in the SBM in the large sample limit. Combining variational approximation and Laplace’s method, a consistent criterion of the fully marginalized loglikelihood is established. Based on that, we derive a tractable algorithm… CONTINUE READING