Learning Theory and Kernel Machines: 16th Annual Conference on Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003 Washington, DC, USA, August ... 2777 (Lecture Notes in Computer Science) - Softcover

 
9783540407201: Learning Theory and Kernel Machines: 16th Annual Conference on Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003 Washington, DC, USA, August ... 2777 (Lecture Notes in Computer Science)
Softcover
ISBN 10: 3540407200 ISBN 13: 9783540407201
Verlag: Springer, 2009

Inhaltsangabe

This volume contains papers presented at the joint 16th Annual Conference on Learning Theory (COLT) and the 7th Annual Workshop on Kernel Machines, heldinWashington,DC,USA,duringAugust24-27,2003.COLT,whichrecently merged with EuroCOLT, has traditionally been a meeting place for learning theorists. We hope that COLT will bene?t from the collocation with the annual workshoponkernelmachines,formerlyheldasaNIPSpostconferenceworkshop. The technical program contained 47 papers selected from 92 submissions. All 47paperswerepresentedasposters;22ofthepaperswereadditionallypresented astalks.Therewerealsotwotargetareaswithinvitedcontributions.Incompu- tional game theory,atutorialentitled"LearningTopicsinGame-TheoreticDe- sionMaking"wasgivenbyMichaelLittman,andaninvitedpaperon"AGeneral Class of No-Regret Learning Algorithms and Game-Theoretic Equilibria" was contributed by Amy Greenwald. In natural language processing, a tutorial on "Machine Learning Methods in Natural Language Processing" was presented by Michael Collins, followed by two invited talks, "Learning from Uncertain Data" by Mehryar Mohri and "Learning and Parsing Stochastic Uni?cation- Based Grammars" by Mark Johnson. In addition to the accepted papers and invited presentations, we solicited short open problems that were reviewed and included in the proceedings. We hope that reviewed open problems might become a new tradition for COLT. Our goal was to select simple signature problems whose solutions are likely to inspire further research. For some of the problems the authors o?ered monetary rewards. Yoav Freund acted as the open problem area chair. The open problems were presented as posters at the conference.

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Reseña del editor

This volume contains papers presented at the joint 16th Annual Conference on Learning Theory (COLT) and the 7th Annual Workshop on Kernel Machines, heldinWashington,DC,USA,duringAugust24-27,2003.COLT,whichrecently merged with EuroCOLT, has traditionally been a meeting place for learning theorists. We hope that COLT will bene?t from the collocation with the annual workshoponkernelmachines,formerlyheldasaNIPSpostconferenceworkshop. The technical program contained 47 papers selected from 92 submissions. All 47paperswerepresentedasposters;22ofthepaperswereadditionallypresented astalks.Therewerealsotwotargetareaswithinvitedcontributions.Incompu- tional game theory,atutorialentitled"LearningTopicsinGame-TheoreticDe- sionMaking"wasgivenbyMichaelLittman,andaninvitedpaperon"AGeneral Class of No-Regret Learning Algorithms and Game-Theoretic Equilibria" was contributed by Amy Greenwald. In natural language processing, a tutorial on "Machine Learning Methods in Natural Language Processing" was presented by Michael Collins, followed by two invited talks, "Learning from Uncertain Data" by Mehryar Mohri and "Learning and Parsing Stochastic Uni?cation- Based Grammars" by Mark Johnson. In addition to the accepted papers and invited presentations, we solicited short open problems that were reviewed and included in the proceedings. We hope that reviewed open problems might become a new tradition for COLT. Our goal was to select simple signature problems whose solutions are likely to inspire further research. For some of the problems the authors o?ered monetary rewards. Yoav Freund acted as the open problem area chair. The open problems were presented as posters at the conference.

Reseña del editor

This book constitutes the joint refereed proceedings of the 16th Annual Conference on Computational Learning Theory, COLT 2003, and the 7th Kernel Workshop, Kernel 2003, held in Washington, DC in August 2003. The 47 revised full papers presented together with 5 invited contributions and 8 open problem statements were carefully reviewed and selected from 92 submissions. The papers are organized in topical sections on kernel machines, statistical learning theory, online learning, other approaches, and inductive inference learning.

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Verlag
Springer
Erscheinungsdatum
2009
Sprache
Englisch
ISBN 10 
3540407200
ISBN 13 
9783540407201
Einband
Tapa blanda
Anzahl der Seiten
768
Herausgeber
Schölkopf Bernhard
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
CMN Printpool Inh. Mathis Neumann
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