Long and Medium-Term Research: Information-Based Approachesto Learning Relational Concepts

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This award is under the Long and Medium-Term Research at Foreign Centers of Excellence Program, which enables U.S. scientists and engineers to conduct three to twelve months of research abroad at research centers of proven excellence. The program's awards provide opportunities for joint research, and the use of unique or complementary facilities, expertise and experimental conditions abroad. This award will support a three-month postdoctoral research visit by Dr. Michael Pazzani of the University of California, Irvine to work with Dr. J. Ross Quinlan of the University of Sydney. Dr. Pazzani will collaborate with Dr. Quinlan on the following topics involving information-based approaches to relational concept learning: A. Investigating approaches to dealing with noise in training data. He will investigate refinements of a Minimum Description Length approach, as well as alternative approaches to dealing with noisy training data. One alternative that will be explored is the technique of averaging multiple models. B. Applying relational concept learning to larger problems on naturally occurring data sets, identifying additional research issues, and examining how well the complexity analysis in Pazzani & Kibler (in press) predicts how the learning methods will scale to larger problems. The award recommendation provides funds to cover international travel and a stipend for three months.