https://wiki.santafe.edu/index.php?title=Airoldi_abs&feed=atom&action=historyAiroldi abs - Revision history2020-10-29T02:23:07ZRevision history for this page on the wikiMediaWiki 1.32.0https://wiki.santafe.edu/index.php?title=Airoldi_abs&diff=16418&oldid=prevAaronc at 18:49, 24 October 20082008-10-24T18:49:54Z<p></p>
<p><b>New page</b></p><div>{{Statistical Inference for Complex Networks}}<br />
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'''Statistical Inference for Complex Networks''' Workshop, December 3-5, 2008, Santa Fe NM<br />
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'''Organizers:''' [http://www.santafe.edu/~aaronc/ Aaron Clauset] (SFI) and [http://www.santafe.edu/~moore/ Cris Moore] (UNM & SFI)<br />
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'''Edo Airoldi''' ([http://www.genomics.princeton.edu/~eairoldi/ homepage])<br />
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''The exchangeable graph model''<br />
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Collections of pairwise measurements arise in a number of settings in the biological sciences (e.g., www.yeastgenome.org), with collections of scientific publications (e.g., www.jstor.org) and other hyper-linked resources (e.g., www.wikipedia.org), and in social networks (e.g., www.linkedin.com). In this talk we introduce the exchangeable graph model, a simple extension of the random graph model by Erdos & Renyi (1959) and Gilbert (1959). The exchangeable graph model can instantiate realistic connectivity patterns, is amenable to mathematical analysis, and preserves phenomena such as the emergence of a giant component. We demonstrate the utility of the exchangeable graph model in solving two open problems in statistical network analysis: 1. model selection among very different statistical models of pairwise measurements, and 2. assessing the statistical significance associated with the observed overlap of independent cliques in a graph.</div>Aaronc