Fetching the paper…
Reading the bibliography…
Many algorithms have been proposed for fitting network models with communities, but most of them do not scale well to large networks, and often fail on sparse networks.
Rohe, KarlK., Chatterjee, SouravS. andYu, BinB. (2011). Spectral clustering and the high-dimensional stochastic blockmodel. Ann. Statist. 39 1878–1915
1915
Earlier work this paper cites.
Hoeffding, WassilyW. (1956). On the distribution of the number of successes in independent trials. Ann. Math. Statist. 27 713–721
1956
Earlier work this paper cites.
Besag, JulianJ. (1974). Spatial interaction and the statistical analysis of lattice systems. J. R. Stat. Soc. Ser. B Stat. Methodol. 36 192–236
1974
Earlier work this paper cites.
Gleser, Leon JayL. J. (1975). On the distribution of the number of successes in independent trials. Ann. Probab. 3 182–188
1975
Earlier work this paper cites.
Holland, Paul W.P. W. andLeinhardt, SamuelS. (1981). An exponential family of probability distributions for directed graphs. J. Amer. Statist. Assoc. 76 33–65
1981
Earlier work this paper cites.
Holland, Paul W.P. W., Laskey, Kathryn BlackmondK. B. andLeinhardt, SamuelS. (1983). Stochastic blockmodels: First steps. Social Networks 5 109–137
1983
Earlier work this paper cites.
Wu, C. F. JeffC. F. J. (1983). On the convergence properties of the EM algorithm. Ann. Statist. 11 95–103
1983
Earlier work this paper cites.
Wang, Yuchung J.Y. J. andWong, George Y.G. Y. (1987). Stochastic blockmodels for directed graphs. J. Amer. Statist. Assoc. 82 8–19
1987
Earlier work this paper cites.
Snijders, Tom A. B.T. A. B. andNowicki, KrzysztofK. (1997). Estimation and prediction for stochastic blockmodels for graphs with latent block structure. J. Classification 14 75–100
1997
Earlier work this paper cites.
Shi, J.J. andMalik, J.J. (2000). Normalized cuts and image segmentation. IEEE Trans. Pattern Analysis and Machine Intelligence 22 888–905
2000
Earlier work this paper cites.
Nowicki, KrzysztofK. andSnijders, Tom A. B.T. A. B. (2001). Estimation and prediction for stochastic blockstructures. J. Amer. Statist. Assoc. 96 1077–1087
2001
Earlier work this paper cites.
Yao, Y. Y.Y. Y. (2003). Information-theoretic measures for knowledge discovery and data mining. In Entropy Measures, Maximum Entropy Principle and Emerging Applications 115–136. Springer, New York
2003
Earlier work this paper cites.
Newman, M. E. J.M. E. J. (2004). Detecting community structure in networks. Eur. Phys. J. B 38 321–330
2004
Earlier work this paper cites.
Newman, M. E. J.M. E. J. andGirvan, M.M. (2004). Finding and evaluating community structure in networks. Phys. Rev. E (3) 69 026113
2004
Cited alongside, same era.
Adamic, L. A.L. A. andGlance, N.N. (2005). The political blogosphere and the 2004 US election. In Proceedings of the WWW-2005 Workshop on the Weblogging Ecosystem. ACM, New York
2005
Cited alongside, same era.
Newman, M. E. J.M. E. J. (2006). Finding community structure in networks using the eigenvectors of matrices. Phys. Rev. E (3) 74 036104, 19
2006
Cited alongside, same era.
Newman, M. E. J.M. E. J. (2006). Modularity and community structure in networks. Proc. Natl. Acad. Sci. USA 103 8577–8582
2006
Cited alongside, same era.
Bickel, Peter J.P. J. andDoksum, Kjell A.K. A. (2007). Mathematical Statistics: Basic Ideas and Selected Topics, 2nd ed. Prentice Hall, New York
2007
2011
Later among the works it cites.
Karrer, BrianB. andNewman, M. E. J.M. E. J. (2011). Stochastic blockmodels and community structure in networks. Phys. Rev. E (3) 83 016107, 10
2011
Later among the works it cites.
2012
Closest in time.
Celisse, AlainA., Daudin, Jean-JacquesJ.-J. andPierre, LaurentL. (2012). Consistency of maximum-likelihood and variational estimators in the stochastic block model. Electron. J. Stat. 6 1847–1899
2012
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Handcock, Mark S.M. S., Raftery, Adrian E.A. E. andTantrum, Jeremy M.J. M. (2007). Model-based clustering for social networks. J. Roy. Statist. Soc. Ser. A 170 301–354
2007
Cited alongside, same era.
Hoff, P. D.P. D. (2007). Modeling homophily and stochastic equivalence in symmetric relational data. In Advances in Neural Information Processing Systems, Vol. 19. MIT Press, Cambridge, MA
2007
Cited alongside, same era.
Newman, M. E. J.M. E. J. andLeicht, E. A.E. A. (2007). Mixture models and exploratory analysis in networks. Proc. Natl. Acad. Sci. USA 104 9564–9569
2007
Cited alongside, same era.
Bickel, P. J.P. J. andChen, A.A. (2009). A nonparametric view of network models and Newman–Girvan and other modularities. Proc. Natl. Acad. Sci. USA 106 21068–21073
2009
Cited alongside, same era.
Fortunato, SantoS. (2010). Community detection in graphs. Phys. Rep. 486 75–174
2010
Cited alongside, same era.
Mariadassou, MahendraM., Robin, StéphaneS. andVacher, CorinneC. (2010). Uncovering latent structure in valued graphs: A variational approach. Ann. Appl. Stat. 4 715–742
2010
Cited alongside, same era.
Ball, B.B., Karrer, B.B. andNewman, M. E. J.M. E. J. (2011). An efficient and principled method for detecting communities in networks. Phys. Rev. E (3) 34 036103
2011
Cited alongside, same era.
2012
Closest in time.
Chaudhuri, KamalikaK., Chung, FanF. andTsiatas, AlexanderA. (2012). Spectral clustering of graphs with general degrees in the extended planted partition model. JMLR Workshop and Conference Proceedings 23 35.1–35.23
2012
Closest in time.
Decelle, A.A., Krzakala, F.F., Moore, C.C. andZdeborová, L.L. (2012). Asymptotic analysis of the stochastic block model for modular networks and its algorithmic applications. Phys. Rev. E (3) 84 066106
2012
Closest in time.
2012
Closest in time.
Perry, P. O.P. O. andWolfe, P. J.P. J. (2012). Null models for network data. Available at \arxivurl
2012
Closest in time.
Zhao, YunpengY., Levina, ElizavetaE. andZhu, JiJ. (2012). Consistency of community detection in networks under degree-corrected stochastic block models. Ann. Statist. 40 2266–2292
2012
Closest in time.
Amini, A. A.A. A., Chen, A.A., Bickel, P. J.P. J. andLevina, E.E. (2013). Supplement to “Pseudo-likelihood methods for community detection in large sparse networks.” DOI: \doiurl
2013
Closest in time.
Airoldi, E. M.E. M., Blei, D. M.D. M., Fienberg, S. E.S. E. andXing, E. P.E. P. (2008). Mixed membership stochastic blockmodels. J. Mach. Learn. Res. 9 1981–2014
2014
Closest in time.