CFP

IJCAI-2003 Workshop
Learning Statistical Models from Relational Data
Monday, 11 August 2003
Acapulco, Mexico
http://kdl.cs.umass.edu/events/srl2003/

This workshop will explore approaches to learning statistical models from relational data. The workshop will explore the foundations, advantages, and limitations of the surprising array of approaches that have been developed over the past decade. These include probabilistic relational models, stochastic logic programs, Bayesian logic programs, relational Bayesian networks, relational probability trees, first-order Bayesian classifiers, relational Markov models, block models and statistical relational models.

These techniques have been developed in several related, but different, subareas of artificial intelligence (reasoning under uncertainty, inductive logic programming, machine learning, and knowledge discovery and data mining) and in some areas outside of AI (e.g., databases and social network analysis). Most researchers only have exposure to one or two techniques, and no clear understanding of the relative advantages and limitations of different techniques has yet emerged. We believe this is an ideal time for a workshop that allows active researchers in this area to discuss and debate the unique challenges of learning statistical models from relational data.

Important Dates

Mar 7, 2003 Submission deadline
Mar 21, 2003 Acceptance notification
May 16, 2003 Camera-ready version of papers

Organizing Chairs

Lise Getoor (co-chair)
http://www.cs.umd.edu/~getoor
getoor@cs.umd.edu

David Jensen (co-chair)
http://www.cs.umass.edu/~jensen
jensen@cs.umass.edu

Additional information: http://kdl.cs.umass.edu/events/srl2003/