Likelihood-based model selection for stochastic block models

[author] Rohe, K.K., Chatterjee, S.S. and Yu, B.B. (2011). Spectral clustering and the high-dimensional stochastic block model. Ann. Statist. 39 1878-1915. \endbibitem

1915

Earlier work this paper cites.

[author] Bickel, PeterP., Choi, DavidD., Chang, XiangyuX. and Zhang, HaiH. (2013). Asymptotic normality of maximum likelihood and its variational approximation for stochastic blockmodels. Ann. Statist. 41 1922–1943. \endbibitem

1943

Earlier work this paper cites.

[author] Holland, P. W.P. W., Laskey, K. B.K. B. and Leinhardt, S.S. (1983). Stochastic blockmodels: First steps. Soc. Netw. 5 109-137. \endbibitem

1983

Earlier work this paper cites.

{binproceedings}

2004

Earlier work this paper cites.

[author] Daudin, J. J.J. J., Picard, F.F. and Robin, S.S. (2008). A mixture model for random graphs. Stat. Comput. 18 173-183. \endbibitem

2008

Earlier work this paper cites.

[author] Bickel, P.P. and Chen, A.A. (2009). A nonparametric view of network models and Newman-Girvan and other modularities. Proc. Natl. Acad. Sci. USA 106 21068-73. \endbibitem

2009

Earlier work this paper cites.

[author] Ball, BB., Karrer, BB. and Newman, M E JM. E. J. (2011). An efficient and principled method for detecting communities in networks. Physical ReviewE 84 036103. \endbibitem

2011

Earlier work this paper cites.

[author] Decelle, AurelienA., Krzakala, FlorentF., Moore, CristopherC. and Zdeborová, LenkaL. (2011). Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications. Phys. Rev. E 84 066106. \endbibitem

2011

Earlier work this paper cites.

[author] Karrer, BrianB. and Newman, M. E. J.M. E. J. (2011). Stochastic blockmodels and community structure in networks. Phys. Rev. E 83 016107. \endbibitem

2011

Earlier work this paper cites.

[author] Zhao, YunpengY., Levina, ElizavetaE. and Zhu, JiJ. (2011). Community extraction for social networks. Proc. Natl. Acad. Sci. USA 108 7321–7326. \endbibitem

2011

Cited alongside, same era.

[author] Celisse, AlainA., Daudin, Jean-JacquesJ.-J., Pierre, LaurentL. et al. (2012). Consistency of maximum-likelihood and variational estimators in the stochastic block model. Electron. J. Stat. 6 1847–1899. \endbibitem

2012

Cited alongside, same era.

[author] Choi, David SD. S., Wolfe, Patrick JP. J. and Airoldi, Edoardo ME. M. (2012). Stochastic blockmodels with a growing number of classes. Biometrika asr053. \endbibitem

2012

Cited alongside, same era.

[author] Latouche, PierreP., Birmele, EtienneE. and Ambroise, ChristopheC. (2012). Variational Bayesian inference and complexity control for stochastic block models. Stat. Modelling 12 93–115. \endbibitem

2012

Cited alongside, same era.

[author] Peixoto, Tiago PT. P. (2013). Parsimonious module inference in large networks. Phys. Rev. Lett. 110 148701. \endbibitem

2013

Later among the works it cites.

[author] Wolfe, Patrick JP. J. and Olhede, Sofia CS. C. (2013). Nonparametric graphon estimation. arXiv preprint arXiv:1309.5936. \endbibitem

Original

2013

Later among the works it cites.

[author] Airoldi, Edoardo M.E. M., Blei, David M.D. M., Fienberg, Stephen E.S. E. and Xing, Eric P.E. P. (2008). Mixed membership stochastic blockmodels. J. Mach. Learn. Res. 9 1981-2014. \endbibitem

2014

Later among the works it cites.

[author] Chen, KehuiK. and Lei, JingJ. (2014). Network cross-validation for determining the number of communities in network data. arXiv preprint arXiv:1411.1715. \endbibitem

Original

2014

Later among the works it cites.

[author] Lei, JingJ. (2014). A Goodness-of-fit Test for Stochastic Block Models. arXiv preprint arXiv:1412.4857. \endbibitem