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Regularized Spectral Clustering under the Degree-Corrected Stochastic Blockmodel
Spectral clustering is a fast and popular algorithm for finding clusters in networks.
The blessing of transitivity in sparse and stochastic networks
The only constraint on the ambient graph is that it is large and sparse--it could be generated at random or by an adversary--suggesting a theoretical explanation for the robust empirical performance of local clustering algorithms.
Co-clustering for directed graphs: the Stochastic co-Blockmodel and spectral algorithm Di-Sim
In each example, a small subset of nodes have persistent asymmetries; these nodes send edges with one cluster, but receive edges with another cluster.
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