Community Detection in Degree-Corrected Block Models

@article{Gao2016CommunityDI,
  title={Community Detection in Degree-Corrected Block Models},
  author={C. Gao and Zongming Ma and A. Zhang and Harrison H. Zhou},
  journal={ArXiv},
  year={2016},
  volume={abs/1607.06993}
}
Community detection is a central problem of network data analysis. Given a network, the goal of community detection is to partition the network nodes into a small number of clusters, which could often help reveal interesting structures. The present paper studies community detection in Degree-Corrected Block Models (DCBMs). We first derive asymptotic minimax risks of the problem for a misclassification proportion loss under appropriate conditions. The minimax risks are shown to depend on degree… Expand

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