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Algorithmic Learning Theory - 13th International Conference, ALT 2002, Lubeck, Germany, November 24-26, 2002, Proceedings (Paperback, 2002 ed.)
Nicolo Cesa-Bianchi, Masayuki Numao, Rudiger Reischuk
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R1,743
Discovery Miles 17 430
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 13th International Conference on Algorithmic Learning Theory, ALT 2002, held in Lübeck, Germany in November 2002. The 26 revised full papers presented together with 5 invited contributions and an introduction were carefully reviewed and selected from 49 submissions. The papers are organized in topical sections on learning Boolean functions, boosting and margin-based learning, learning with queries, learning and information extraction, inductive inference, inductive logic programming, language learning, statistical learning, and applications and heuristics.
This important new text and reference for researchers and students
in machine learning, game theory, statistics and information theory
offers the first comprehensive treatment of the problem of
predicting individual sequences. Unlike standard statistical
approaches to forecasting, prediction of individual sequences does
not impose any probabilistic assumption on the data-generating
mechanism. Yet, prediction algorithms can be constructed that work
well for all possible sequences, in the sense that their
performance is always nearly as good as the best forecasting
strategy in a given reference class. The central theme is the model
of prediction using expert advice, a general framework within which
many related problems can be cast and discussed. Repeated game
playing, adaptive data compression, sequential investment in the
stock market, sequential pattern analysis, and several other
problems are viewed as instances of the experts' framework and
analyzed from a common nonstochastic standpoint that often reveals
new and intriguing connections. Old and new forecasting methods are
described in a mathematically precise way in order to characterize
their theoretical limitations and possibilities.
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