Technical Reports

The ICICS/CS Reading Room

UBC CS TR-2009-08 Summary

Learning a contingently acyclic, probabilistic relational model of a social network, April 06, 2009 Peter Carbonetto, Jacek Kisynski, Michael Chiang and David Poole, 14 pages

We demonstrate through experimental comparisons that modeling relations in a social network with a directed probabilistic model provides a viable alternative to the standard undirected graphical model approach. Our model incorporates special latent variables to guarantee acyclicity. We investigate the inference and learning challenges entailed by our approach.

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