Titlebook: Statistical Network Analysis: Models, Issues, and New Directions; ICML 2006 Workshop o Edoardo Airoldi,David M. Blei,Alice X. Zheng Confere

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Combining Stochastic Block Models and Mixed Membership for Statistical Network Analysisto examine two data sets. (1) a collection of sociometric relations among monks is used to investigate the crisis that took place in a monastery [2], and (2) data from a school-based longitudinal study of the health-related behaviors of adolescents. Both data sets have recently been reanalyzed in [3

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Learning Approximate MRFs from Large Transactional Dataperimental results). Translated into the social network domain, this is the problem of computing the likelihood of seeing a particular combination of grocery items in the market basket domain, or the probability of a group of professors coauthoring a paper in a co-authorship network, etc. This margi

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0302-9743 e in particular deserve special recognition. Anna Goldenberg and Alice Zheng were the driving force behind the entire enterprise and Edo Airoldi assisted on a number of the more important arrangements.978-3-540-73132-0978-3-540-73133-7Series ISSN 0302-9743 Series E-ISSN 1611-3349

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https://doi.org/10.1007/978-3-540-73133-7Online; calculus; distributed networks; dynamical networks; evolving networks; genetic algorithms; graph d

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Discrete Temporal Models of Social NetworksGMs). Many of the methods for ERGMs are readily adapted for these models, including MCMC maximum likelihood estimation algorithms. We discuss models of this type and give examples, as well as a demonstration of their use for hypothesis testing and classification.

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