Learning Theory 18th Annual Conference on Learning Theory, COLT 2005
This volume contains papers presented at the Eighteenth Annual Conference on Learning Theory (previously known as the Conference on Computational Learning Theory) held in Bertinoro, Italy from June 27 to 30, 2005. The technical program contained 45 papers
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Subseries of Lecture Notes in Computer Science
3559
Peter Auer Ron Meir (Eds.)
Learning Theory 18th Annual Conference on Learning Theory, COLT 2005 Bertinoro, Italy, June 27-30, 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 Peter Auer University of Leoben Department of Mathematics and Information Technologies Franz-Josef-Strasse 18, 8700 Leoben, Austria E-mail: [email protected] Ron Meir Technion, Israel Institute of Technology Department of Electrical Engineering Haifa 3200, P.O. Box, Israel E-mail: [email protected]
Library of Congress Control Number: 2005927736
CR Subject Classification (1998): I.2.6, I.2.3, I.2, F.4.1, F.2, F.1.1 ISSN ISBN-10 ISBN-13
0302-9743 3-540-26556-2 Springer Berlin Heidelberg New York 978-3-540-26556-6 Springer Berlin Heidelberg New York
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Preface
This volume contains papers presented at the Eighteenth Annual Conference on Learning Theory (previously known as the Conference on Computational Learning Theory) held in Bertinoro, Italy from June 27 to 30, 2005. The technical program contained 45 papers selected from 120 submissions, 3 open problems selected from among 5 contributed, and 2 invited lectures. The invited lectures were given by Sergiu Hart on “Uncoupled Dynamics and Nash Equilibrium”, and by Satinder Singh on “Rethinking State, Action, and Reward in Reinforcement Learning”. These papers were not included in this volume. The Mark Fulk Award is presented annually for the best paper co-authored by a student. The student selected this year was Hadi Salmasian for the paper titled “The Spectral Method for General Mixture Models” co-authored with Ravindran Kannan and Santosh Vempala. The number of papers submitted to COLT this year was exceptionally high. In addition to the classical COLT topics, we found an increase in the number of submissions related to novel classification scenarios such as ranking. This increase reflects a healthy shift towards more structured classification problems, which are becoming increasingly relevant to practitioners. The large number of quality sub
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