Model Selection for Degree-corrected Block Models

17 Jul 2012Xiaoran YanCosma Rohilla ShaliziJacob E. JensenFlorent KrzakalaCristopher MooreLenka ZdeborovaPan ZhangYaojia Zhu

The proliferation of models for networks raises challenging problems of model selection: the data are sparse and globally dependent, and models are typically high-dimensional and have large numbers of latent variables. Together, these issues mean that the usual model-selection criteria do not work properly for networks... (read more)

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