SRL2006: Open Problems in Statistical Relational Learning
ICML 2006 Workshop
Thursday June 29, 2006
|Call For Papers
Statistical relational learning (SRL) addresses the challenge of applying statistical inference to problems which involve rich collections of objects linked together in complex relational networks. The last decade of SRL research has explored many different ways to combine statistical and relational models. We now have a much improved understanding of the strengths and weaknesses of various SRL representation languages, and have software systems for learning both model structure and parameters. The goal of this workshop is to look forward to the next five years of SRL research. What are the open problems and challenges? Some new problems have become clear through practical experience; other problems were hinted at in early SRL work and still seem daunting today. With the shared vocabulary and experience that the SRL community has developed, we expect be able to formulate the important research problems much more precisely than we could five or ten years ago. Because our goal is to look forward, the bulk of the workshop will be organized into open problem sessions with focused discussion and contributed presentations.