TY - BOOK ID - 5401508 TI - Prediction, learning, and games AU - Cesa-Bianchi, Nicolò AU - Lugosi, Gábor PY - 2006 SN - 0521841089 9780521841085 9780511546921 0511191782 9780511191787 0511546920 0511189958 9780511189951 051119059X 9780511190599 0511190913 9780511190919 0511191316 9780511191312 1107162955 1280458356 9786610458356 051131602X PB - Cambridge : Cambridge University Press, DB - UniCat KW - Game theory. KW - Machine learning. KW - Computer algorithms. KW - Théorie des jeux KW - Apprentissage automatique KW - Algorithmes KW - Théorie des jeux KW - Algorithms KW - Learning, Machine KW - Artificial intelligence KW - Machine theory KW - Games, Theory of KW - Theory of games KW - Mathematical models KW - Mathematics UR - https://www.unicat.be/uniCat?func=search&query=sysid:5401508 AB - This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a 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. ER -