Difference between revisions of "10-601 Network Models"
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=== Slides === | === Slides === | ||
| − | [http://curtis.ml.cmu.edu/w/courses/images/d/dc/Lecture22-SN.pdf Slides in PDF] | + | * [http://curtis.ml.cmu.edu/w/courses/images/d/dc/Lecture22-SN.pdf Slides in PDF] |
| + | * Also: [http://www.cs.cmu.edu/~wcohen/10-601/AWS.pptx Slides about Amazon Web Services] | ||
=== Readings === | === Readings === | ||
Latest revision as of 10:46, 18 November 2013
Slides
Readings
E. Airoldi, D. Blei, S. Fienberg, and E. P. Xing,Mixed Membership Stochastic Blockmodel Journal of Machine Learning Research, 9(Sep):1981--2014, 2008.
Taking home message
- Networks can be described by global/local features (what are they?)
- But these features are not helpful for inferring individual nodal information.
- SBM is a probabilistic model for grouping network nodes into communities/clusters, each cluster corresponds to a single "role" or social position
- MMSB is a probabilistic model that allows each node to have multiple roles, and allow each edge to have contextual-dependent role instantiations.
- dMMSB can infer multi-role trajectories for every node.
- Inference of MMSB and dMMSB employs MCMC or VI
