Algorithmic Learning Theory 21st International Conference, ALT 2
This volume contains the papers presented at the 21st International Conf- ence on Algorithmic Learning Theory (ALT 2010), which was held in Canberra, Australia, October 6–8, 2010. The conference was co-located with the 13th - ternational Conference on Dis
- PDF / 6,157,855 Bytes
- 432 Pages / 430 x 660 pts Page_size
- 62 Downloads / 230 Views
Subseries of Lecture Notes in Computer Science
6331
Marcus Hutter Frank Stephan Vladimir Vovk Thomas Zeugmann (Eds.)
Algorithmic Learning Theory 21st International Conference, ALT 2010 Canberra, Australia, October 6-8, 2010 Proceedings
13
Series Editors Randy Goebel, University of Alberta, Edmonton, Canada Jörg Siekmann, University of Saarland, Saarbrücken, Germany Wolfgang Wahlster, DFKI and University of Saarland, Saarbrücken, Germany Volume Editors Marcus Hutter Australian National University and NICTA Research School of Information Sciences and Engineering Canberra, ACT 0200, Australia E-mail: [email protected] Frank Stephan National University of Singapore, Department of Mathematics Block S17, 10 Lower Kent Ridge Road, Singapore 119076, Republic of Singapore E-mail: [email protected] Vladimir Vovk University of London, Department of Computer Science Royal Holloway, Egham, Surrey TW20 0EX, UK E-mail: [email protected] Thomas Zeugmann Hokkaido University, Division of Computer Science N-14, W-9, Sapporo 060-0814, Japan E-mail: [email protected]
Library of Congress Control Number: 2010934948 CR Subject Classification (1998): I.2, F.4.1, F.1, F.2, I.2.3, I.2.6 LNCS Sublibrary: SL 7 – Artificial Intelligence ISSN ISBN-10 ISBN-13
0302-9743 3-642-16107-3 Springer Berlin Heidelberg New York 978-3-642-16107-0 Springer Berlin Heidelberg New York
This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. springer.com © Springer-Verlag Berlin Heidelberg 2010 Printed in Germany Typesetting: Camera-ready by author, data conversion by Scientific Publishing Services, Chennai, India Printed on acid-free paper 06/3180
Preface
This volume contains the papers presented at the 21st International Conference on Algorithmic Learning Theory (ALT 2010), which was held in Canberra, Australia, October 6–8, 2010. The conference was co-located with the 13th International Conference on Discovery Science (DS 2010) and with the Machine Learning Summer School, which was held just before ALT 2010. The technical program of ALT 2010, contained 26 papers selected from 44 submissions and five invited talks. The invited talks were presented in joint sessions of both conferences. ALT 2010 was dedicated to the theoretical foundations of machine learning and took place on the campus of the Australian National University, Canberra, Australia. ALT provides a forum for high-quality talks with a strong theoretical background and scientific interchange in areas such as inductive inference, universal prediction, tea
Data Loading...
