Algorithmic Learning Theory 18th International Conference, ALT 2007,
This volume contains the papers presented at the 18th International Conf- ence on Algorithmic Learning Theory (ALT 2007), which was held in Sendai (Japan) during October 1–4, 2007. The main objective of the conference was to provide an interdisciplinary f
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Subseries of Lecture Notes in Computer Science
4754
Marcus Hutter Rocco A. Servedio Eiji Takimoto (Eds.)
Algorithmic Learning Theory 18th International Conference, ALT 2007 Sendai, Japan, October 1-4, 2007 Proceedings
13
Series Editors Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USA Jörg Siekmann, University of Saarland, Saarbrücken, Germany Volume Editors Marcus Hutter RSISE @ ANU and SML @ NICTA Canberra, ACT, 0200, Australia E-mail: [email protected] Rocco A. Servedio Columbia University New York, NY, USA E-mail: [email protected] Eiji Takimoto Tohoku University Sendai 980-8579, Japan E-mail: [email protected]
Library of Congress Control Number: 2007935310
CR Subject Classification (1998): I.2.6, I.2.3, F.1, F.2, F.4, I.7 LNCS Sublibrary: SL 7 – Artificial Intelligence ISSN ISBN-10 ISBN-13
0302-9743 3-540-75224-2 Springer Berlin Heidelberg New York 978-3-540-75224-0 Springer Berlin Heidelberg New York
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Preface
This volume contains the papers presented at the 18th International Conference on Algorithmic Learning Theory (ALT 2007), which was held in Sendai (Japan) during October 1–4, 2007. The main objective of the conference was to provide an interdisciplinary forum for high-quality talks with a strong theoretical background and scientific interchange in areas such as query models, on-line learning, inductive inference, algorithmic forecasting, boosting, support vector machines, kernel methods, complexity and learning, reinforcement learning, unsupervised learning and grammatical inference. The conference was co-located with the Tenth International Conference on Discovery Science (DS 2007). This volume includes 25 technical contributions that were selected from 50 submissions by the Program Committee. It also contains descriptions of the five invited talks of ALT and DS; longer versions of the DS papers are available in the proceedings of DS 2007. These invited talks were presented to the audience of both conferences in joint sessions. – Avrim Blum (Carnegie Mellon University, Pittsburgh, USA): “A Theory of Similarity Functions for Learning and Clustering” (invited speaker for ALT 2007) – Thomas G. Dietterich (Oreg
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