2008 MixedMembershipStochasticBlockm

• (Airoldi et al., 2008) ⇒ Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, and Eric P. Xing. (2008). “Mixed Membership Stochastic Blockmodels.” In: The Journal of Machine Learning Research, 9.

Subject Headings: Mixed Membership Stochastic Blockmodel, Stochastic Blockmodel.

Notes

• Prior published articles include:
  • (Airoldi et al., 2008a) ⇒ Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, and Eric P. Xing. “Mixed membership stochastic blockmodels.” In: Journal of Machine Learning Research 9, no. 1981-2014 (2008): 3.
  • (Airoldi et al., 2005) ⇒ Edoardo M. Airoldi, David M. Blei, Stephen E. Fienberg, Eric P. Xing, and Tommi Jaakkola. “Mixed membership stochastic block models for relational data with application to protein-protein interactions.” In: Proceedings of the international biometrics society annual meeting. 2006.

Cited By

• http://scholar.google.com/scholar?q=%222008%22+Mixed+Membership+Stochastic+Blockmodels
• http://dl.acm.org/citation.cfm?id=1390681.1442798&preflayout=flat#citedby

Quotes

Abstract

Consider data consisting of pairwise measurements, such as presence or absence of links between pairs of objects. These data arise, for instance, in the analysis of protein interactions and gene regulatory networks, collections of author-recipient email, and social networks. Analyzing pairwise measurements with probabilistic models requires special assumptions, since the usual independence or exchangeability assumptions no longer hold. Here we introduce a class of variance allocation models for pairwise measurements: mixed membership stochastic blockmodels. These models combine global parameters that instantiate dense patches of connectivity (blockmodel) with local parameters that instantiate node-specific variability in the connections (mixed membership). We develop a general variational inference algorithm for fast approximate posterior inference. We demonstrate the advantages of mixed membership stochastic blockmodels with applications to social networks and protein interaction networks.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2008 MixedMembershipStochasticBlockm	Eric P. Xing Stephen E. Fienberg Edoardo M. Airoldi David M. Blei			Mixed Membership Stochastic Blockmodels						2008