Belief propagation, robust reconstruction and optimal recovery of block models

  title={Belief propagation, robust reconstruction and optimal recovery of block models},
  author={Elchanan Mossel and Joe Neeman and Allan Sly},
We consider the problem of reconstructing sparse symmetric block models with two blocks and connection probabilities a=n and b=n for inter- and intra-block edge probabilities respectively. It was recently shown that one can do better than a random guess if and only if (a b) 2 > 2(a + b). Using a variant of Belief Propagation, we give a reconstruction algorithm that is optimal in the sense that if (a b) 2 > C(a + b) for some constant C then our algorithm maximizes the fraction of the nodes… 

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Partial recovery bounds for the sparse stochastic block model

  • J. ScarlettV. Cevher
  • Computer Science, Mathematics
    2016 IEEE International Symposium on Information Theory (ISIT)
  • 2016
The information-theoretic limits of community detection in the symmetric two-community stochastic block model, with intra-community and inter-community edge probabilities a/n and b/n respectively, are studied.

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The Metropolis Algorithm for Graph Bisection

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