A semidefinite program for unbalanced multisection in the stochastic block model

@article{Perry2017ASP,
  title={A semidefinite program for unbalanced multisection in the stochastic block model},
  author={William Perry and Alexander S. Wein},
  journal={2017 International Conference on Sampling Theory and Applications (SampTA)},
  year={2017},
  pages={64-67}
}
We propose a semidefinite programming (SDP) algorithm for community detection in the stochastic block model, a popular model for networks with latent community structure. We prove that our algorithm achieves exact recovery of the latent communities, up to the information-theoretic limits determined by Abbe and Sandon. Our result extends prior SDP approaches by allowing for many communities of different sizes. By virtue of a semidefinite approach, our algorithms succeed against a semirandom… CONTINUE READING
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Performance of a community detection algorithm based on semidefinite programming

  • F. Ricci-Tersenghi, A. Javanmard, A. Montanari
  • In Journal of Physics: Conference Series,
  • 2016

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