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Learning Theory, Proceedings of 17th Annual Conference on Learning Theory, COLT 2004

Learning Theory, Proceedings of 17th Annual Conference on Learning Theory, COLT 2004
Learning Theory, Proceedings of 17th Annual Conference on Learning Theory, COLT 2004
This book constitutes the refereed proceedings of the 17th Annual Conference on Learning Theory, COLT 2004, held in Banff, Canada in July 2004. The 46 revised full papers presented were carefully reviewed and selected from a total of 113 submissions. The papers are organized in topical sections on economics and game theory, online learning, inductive inference, probabilistic models, Boolean function learning, empirical processes, MDL, generalisation, clustering and distributed learning, boosting, kernels and probabilities, kernels and kernel matrices, and open problems.
algorithmic learning, bayesian networks, computational learning, decision theory, game theory, inductive inference, kernel methods, learning theory, machine learning, online learning, statistical learning, support vector machine
Springer
Shawe-Taylor, John
b1931d97-fdd0-4bc1-89bc-ec01648e928b
Singer, Yoram
cdaa68cd-0e57-4809-9823-84c4330e3b36
Shawe-Taylor, John
b1931d97-fdd0-4bc1-89bc-ec01648e928b
Singer, Yoram
cdaa68cd-0e57-4809-9823-84c4330e3b36

Shawe-Taylor, John and Singer, Yoram (eds.) (2004) Learning Theory, Proceedings of 17th Annual Conference on Learning Theory, COLT 2004 (Lecture Notes in Computer Science (LNCS, LNAI), 3120), vol. 3120, Springer

Record type: Book

Abstract

This book constitutes the refereed proceedings of the 17th Annual Conference on Learning Theory, COLT 2004, held in Banff, Canada in July 2004. The 46 revised full papers presented were carefully reviewed and selected from a total of 113 submissions. The papers are organized in topical sections on economics and game theory, online learning, inductive inference, probabilistic models, Boolean function learning, empirical processes, MDL, generalisation, clustering and distributed learning, boosting, kernels and probabilities, kernels and kernel matrices, and open problems.

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More information

Published date: 2004
Keywords: algorithmic learning, bayesian networks, computational learning, decision theory, game theory, inductive inference, kernel methods, learning theory, machine learning, online learning, statistical learning, support vector machine
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 259581
URI: https://eprints.soton.ac.uk/id/eprint/259581
PURE UUID: cbd866c5-2bb2-40d9-a7d5-7c4fb2d1ff23

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Date deposited: 02 Mar 2005
Last modified: 26 Feb 2019 17:32

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Contributors

Editor: John Shawe-Taylor
Editor: Yoram Singer

University divisions

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