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The stochastic block model and its variants have been a popular tool in analyzing large network data with community structures.
Perturbation bounds in connection with singular value decomposition
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Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications
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Spectral clustering of graphs with general degrees in the extended planted partition model
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Universally consistent latent position estimation and vertex classification for random dot product graphs
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Exact recovery in the stochastic block model
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Consistent adjacency-spectral partitioning for the stochastic block model when the model parameters are unknown
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Spectral redemption in clustering sparse networks
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A generic sample splitting approach for refined community recovery in stochastic block models
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Model selection for degree-corrected block models
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Likelihood-based model selection for stochastic block models
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