Michael P. Verdicchio

This semester we’ve covered a number of topics in Sungwook Yoon’s Statistical Relational Learning reading group. My turn came a couple of weeks ago and I presented Bayesian Logic Programming. It is essentially a methodology which combines the structural conveniences of Bayesian networks and the theorem proving aspects of logic programming. The chapter in the Getoor/Taskar text was not especially liked in the group as it lacked, among a number of things, specific examples of its use and advantages; in other words, we didn’t know WHY we should use such a framework, only that it was an interesting hybrid of two seemingly separate methodologies. Nonetheless, my slides are below.

Slides (ppt)