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In the high dimensional Stochastic Blockmodel for a random network, the number of clusters (or blocks) K grows with the number of nodes N.
Stochastic blockmodels: First steps
P.W. Holland and S. Leinhardt · 1983
Earlier work this paper cites.
Neocortex size as a constraint on group size in primates
R.I.M. Dunbar · 1992
Earlier work this paper cites.
Regression shrinkage and selection via the lasso
R. Tibshirani · 1996
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Spectral partitioning of random graphs
F. McSherry · 2001
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Diagnosis of multiple cancer types by shrunken centroids of gene expression
R. Tibshirani, T. Hastie, B. Narasimhan, and G. Chu · 2002
Earlier work this paper cites.
High dimensional covariance matrix estimation using a factor model
J. Fan, Y. Fan, and J. Lv · 2008
Earlier work this paper cites.
Sparse inverse covariance estimation with the graphical lasso
J. Friedman, T. Hastie, and R. Tibshirani · 2008
Earlier work this paper cites.
Statistical properties of community structure in large social and information networks
J. Leskovec, K.J. Lang, A. Dasgupta, and M.W. Mahoney · 2008
Earlier work this paper cites.
A nonparametric view of network models and newman–girvan and other modularities
P.J. Bickel and A. Chen · 2009
Earlier work this paper cites.
Implementing regularization implicitly via approximate eigenvector computation
Michael W Mahoney and Lorenzo Orecchia · 2010
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A unified framework for high-dimensional analysis of m m -estimators with decomposable regularizers
S. Negahban, P. Ravikumar, M.J. Wainwright, and B. Yu · 2010
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The method of moments and degree distributions for network models
P.J. Bickel, A. Chen, and E. Levina · 2011
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Consistency of maximum-likelihood and variational estimators in the stochastic block model
Alain Celisse, J-J Daudin, and Laurent Pierre · 2011
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Classification and estimation in the stochastic block model based on the empirical degrees
Pseudo-likelihood methods for community detection in large sparse networks
Arash A Amini, Aiyou Chen, Peter J Bickel, and Elizaveta Levina · 2012
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P. Bickel, D. Choi, X. Chang, and H. Zhang · 2012
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Spectral clustering of graphs with general degrees in the extended planted partition model
K. Chaudhuri, F. Chung, and A. Tsiatas · 2012
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Stochastic blockmodels with a growing number of classes
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On consistency of community detection in networks
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