Algorithmic Learning Theory 16th International Conference, ALT 2005,
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Subseries of Lecture Notes in Computer Science
3734
Sanjay Jain Hans Ulrich Simon Etsuji Tomita (Eds.)
Algorithmic Learning Theory 16th International Conference, ALT 2005 Singapore, October 8-11, 2005 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 Sanjay Jain National University of Singapore School of Computing, Department of Computer Science 117543 Singapore E-mail: [email protected] Hans Ulrich Simon Ruhr-Universität Bochum Fakultät für Mathematik, Lehrstuhl Mathematik und Informatik 44780 Bochum, Germany E-mail: [email protected] Etsuji Tomita The University of Electro-Communications Department of Information and Communication Engineering Chofugaoka 1–5–1, Chofu, Tokyo 182–8585, Japan E-mail: [email protected]
Library of Congress Control Number: 2005933042
CR Subject Classification (1998): I.2.6, I.2.3, F.1, F.2, F.4, I.7 ISSN ISBN-10 ISBN-13
0302-9743 3-540-29242-X Springer Berlin Heidelberg New York 978-3-540-29242-5 Springer Berlin Heidelberg New York
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Preface
This volume contains the papers presented at the 16th Annual International Conference on Algorithmic Learning Theory (ALT 2005), which was held in Singapore (Republic of Singapore), October 8–11, 2005. The main objective of the conference is to provide an interdisciplinary forum for the discussion of the theoretical foundations of machine learning as well as their relevance to practical applications. The conference was co-located with the 8th International Conference on Discovery Science (DS 2005). The conference was also held in conjunction with the centennial celebrations of the National University of Singapore. The volume includes 30 technical contributions, which were selected by the program committee from 98 submissions. It also contains the ALT 2005 invited talks presented by Chih-Jen Lin (National Taiwan University, Taipei, Taiwan) on “Training Support Vector Machines via SMO-type Decomposition Methods,” and by Vasant Honavar (Iowa State University, Ames, Iowa, USA) on “Algorithms and Software for Collaborative Discovery from Autono
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