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COLT is the leading international conference in learning theory, established in 1988. COLT proceedings present research addressing the theoretical modeling and analysis of all aspects of learning and empirical inference, including: Analysis of learning algorithms and their generalization ability Computational complexity of learning Bayesian analysis Statistical mechanics of learning systems Optimization procedures for learning Inductive inference Boolean function learning Unsupervised and semi-supervised learning and clustering On-line learning and relative loss bounds Learning in planning and control (including reinforcement learning) Mathematical analysis of learning in related fields Additional InformationClick here to view Table of Contents.
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