Machine and Statistical Learning: Prediction and Discovery

Sunday, June 25 - Thursday, June 29, 2006

Organizers:

Joseph S. Verducci, Ohio State University
Xiaotong Shen, Ohio State University
John Lafferty,Carnegie Mellon University

Machine learning is an active and rapidly growing area of research that offers systematic and machine-implementable approaches to extracting information from vast and complex data sources. The goal of this conference was to assemble researchers from the disciplines of computer science and statistics around the topical themes of support vector machines and other large margin classifiers, boosting and ensemble methods, new extensions of classification and regression, methods for approximate inference, and application areas. The conference resulted in a lively exchange between the two communities, which will hopefully lead to cross-fertilization and new collaborations across traditional academic disciplines.

The conference schedule and links to the slides for the presentations are given below.

Web site for the 2006 AMS-IMS-SIAM Summer Research Conferences.
Web site for the 2003 Conference