This book constitutes the refereed proceedings of the 17th International Conference on Algorithmic Learning Theory, ALT 2006, held in Barcelona, Spain in October 2006, colocated with the 9th International Conference on Discovery Science, DS 2006.
The 24 revised full papers presented together with the abstracts of five invited papers were carefully reviewed and selected from 53 submissions. The papers are dedicated to the theoretical foundations of machine learning. They address topics such as query models, on-line learning, inductive inference, algorithmic forecasting, boosting, support vector machines, kernel methods, reinforcement learning, and statistical learning models.
Lecture Notes in Artificial Intelligence Edited by J. G. Carbonell and J. Siekmann
Subseries of Lecture Notes in Computer Science
4264
José L. Balcázar Philip M. Long Frank Stephan (Eds.)
Algorithmic Learning Theory 17th International Conference, ALT 2006 Barcelona, Spain, October 7-10, 2006 Proceedings
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Series Editors Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USA Jörg Siekmann, University of Saarland, Saarbrücken, Germany Volume Editors José L. Balcázar Universitat Politecnica de Catalunya, Dept. Llenguatges i Sistemes Informatics c/ Jordi Girona, 1-3, 08034 Barcelona, Spain E-mail:
[email protected] Philip M. Long Google 1600 Amphitheatre Parkway, Mountain View, CA 94043, USA E-mail:
[email protected] Frank Stephan National University of Singapore, Depts. of Mathematics and Computer Science 2 Science Drive 2, Singapore 117543, Singapore E-mail: