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Learning Theory: 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings
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Learning Theory: 17th Annual Conference on Learning Theory, COLT 2004, Banff, Canada, July 1-4, 2004, Proceedings (Paperback)

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Synopsis

This volume contains papers presented at the 17th Annual Conference on Le- ning Theory (previously known as the Conference on Computational Learning Theory) held in Ban?, Canada from July 1 to 4, 2004. The technical program contained 43 papers selected from 107 submissions, 3 open problems selected from among 6 contributed, and 3 invited lectures. The invited lectures were given by Michael Kearns on 'Game Theory, Automated Trading and Social Networks', Moses Charikar on 'Algorithmic Aspects of - nite Metric Spaces', and Stephen Boyd on 'Convex Optimization, Semide?nite Programming, and Recent Applications'. These papers were not included in this volume. The Mark Fulk Award is presented annually for the best paper co-authored by a student. Thisyear theMark Fulk award wassupplemented with two further awards funded by the Machine Learning Journal and the National Information Communication Technology Centre, Australia (NICTA). We were therefore able toselectthreestudentpapersforprizes.ThestudentsselectedwereMagalieF- montforthesingle-authorpaper"ModelSelectionbyBootstrapPenalizationfor Classi?cation", Daniel Reidenbach for the single-author paper "On the Lear- bility of E-Pattern Languages over Small Alphabets", and Ran Gilad-Bachrach for the paper "Bayes and Tukey Meet at the Center Point" (co-authored with Amir Navot and Naftali Tishby).

Computing & ITComputer scienceArtificial intelligenceMachine learning Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Publication Date: 17/06/2004 ISBN-13: 9783540222828  Details: Type: Paperback Format: Books
Availability: Printed to order. Despatched in 2-3 weeks.  

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