NICOLO CESA BIANCHI (31 risultati)

Hardcover. Condizione: Very Good. No Jacket. Hardcover 2002 library bound edition. Ex-library book with stamps and labels attached. Binding firm. Pages unmarked and clean. Laminated covers and text in very good condition. Series : Lecture Notes in Artificial Intelligence ;2533. [xi, 413 p. ; 24 cm].

Paperback. Condizione: Very Good. Ex-library paperback in very nice condition with the usual markings and attachments.

hardcover. Condizione: Fine.

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hardcover. Condizione: New. In shrink wrap. Looks like an interesting title!

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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume contains the papers presented at the 13th Annual Conference on Algorithmic Learning Theory (ALT 2002), which was held in Lub eck (Germany) during November 24-26, 2002. The main objective of the conference was to p- vide an interdisciplinary forum discussing the theoretical foundations of machine learning as well as their relevance to practical applications. The conference was colocated with the Fifth International Conference on Discovery Science (DS 2002). The volume includes 26 technical contributions which were selected by the program committee from 49 submissions. It also contains the ALT 2002 invited talks presented by Susumu Hayashi (Kobe University, Japan) on 'Mathematics Based on Learning', by John Shawe-Taylor (Royal Holloway University of L- don, UK) on 'On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum', and by Ian H. Witten (University of Waikato, New Zealand) on 'Learning Structure from Sequences, with Applications in a Digital Library' (joint invited talk with DS 2002). Furthermore, this volume - cludes abstracts of the invited talks for DS 2002 presented by Gerhard Widmer (Austrian Research Institute for Arti cial Intelligence, Vienna) on 'In Search of the Horowitz Factor: Interim Report on a Musical Discovery Project' and by Rudolf Kruse (University of Magdeburg, Germany) on 'Data Mining with Graphical Models'. The complete versions of these papers are published in the DS 2002 proceedings (Lecture Notes in Arti cial Intelligence, Vol. 2534). ALT has been awarding the E.

Condizione: As New. Unread book in perfect condition.

Hardback. Condizione: New. 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.

Taschenbuch. Condizione: Neu. Algorithmic Learning Theory | 13th International Conference, ALT 2002, Lübeck, Germany, November 24-26, 2002, Proceedings | Nicolò Cesa-Bianchi (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2002 | Springer | EAN 9783540001706 | Verantwortliche Person für die EU: Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg, productsafety[at]springernature[dot]com | Anbieter: preigu.

Softcover. Condizione: Gut. Gebraucht - Gut Zustand: Gut, XI, 415 p. About this book 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. Written for research and development professionals.

Hardcover. Condizione: Brand New. new title edition. 406 pages. 10.00x7.00x1.00 inches. In Stock.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condizione: As New. Unread book in perfect condition.

paperback. Condizione: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Hardback. Condizione: New. 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.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This volume contains the papers presented at the 13th Annual Conference on Algorithmic Learning Theory (ALT 2002), which was held in Lub eck (Germany) during November 24-26, 2002. The main objective of the conference was to p- vide an interdisciplinary forum discussing the theoretical foundations of machine learning as well as their relevance to practical applications. The conference was colocated with the Fifth International Conference on Discovery Science (DS 2002). The volume includes 26 technical contributions which were selected by the program committee from 49 submissions. It also contains the ALT 2002 invited talks presented by Susumu Hayashi (Kobe University, Japan) on 'Mathematics Based on Learning', by John Shawe-Taylor (Royal Holloway University of L- don, UK) on 'On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum', and by Ian H. Witten (University of Waikato, New Zealand) on 'Learning Structure from Sequences, with Applications in a Digital Library' (joint invited talk with DS 2002). Furthermore, this volume - cludes abstracts of the invited talks for DS 2002 presented by Gerhard Widmer (Austrian Research Institute for Arti cial Intelligence, Vienna) on 'In Search of the Horowitz Factor: Interim Report on a Musical Discovery Project' and by Rudolf Kruse (University of Magdeburg, Germany) on 'Data Mining with Graphical Models'. The complete versions of these papers are published in the DS 2002 proceedings (Lecture Notes in Arti cial Intelligence, Vol. 2534). ALT has been awarding the E. 432 pp. Englisch.

Hardcover. Condizione: new. Hardcover. 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. The central theme here is a model of prediction using expert advice, a general framework within which many related problems can be cast and discussed, including repeated game playing, adaptive data compression, sequential investment in the stock market, and sequential pattern analysis. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Hardcover. Condizione: Brand New. new title edition. 406 pages. 10.00x7.00x1.00 inches. In Stock. This item is printed on demand.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This volume contains the papers presented at the 13th Annual Conference on Algorithmic Learning Theory (ALT 2002), which was held in Lub ¿ eck (Germany) during November 24¿26, 2002. The main objective of the conference was to p- vide an interdisciplinary forum discussing the theoretical foundations of machine learning as well as their relevance to practical applications. The conference was colocated with the Fifth International Conference on Discovery Science (DS 2002). The volume includes 26 technical contributions which were selected by the program committee from 49 submissions. It also contains the ALT 2002 invited talks presented by Susumu Hayashi (Kobe University, Japan) on ¿Mathematics Based on Learning¿, by John Shawe-Taylor (Royal Holloway University of L- don, UK) on ¿On the Eigenspectrum of the Gram Matrix and Its Relationship to the Operator Eigenspectrum¿, and by Ian H. Witten (University of Waikato, New Zealand) on ¿Learning Structure from Sequences, with Applications in a Digital Library¿ (joint invited talk with DS 2002). Furthermore, this volume - cludes abstracts of the invited talks for DS 2002 presented by Gerhard Widmer (Austrian Research Institute for Arti cial Intelligence, Vienna) on ¿In Search of the Horowitz Factor: Interim Report on a Musical Discovery Project¿ and by Rudolf Kruse (University of Magdeburg, Germany) on ¿Data Mining with Graphical Models¿. The complete versions of these papers are published in the DS 2002 proceedings (Lecture Notes in Arti cial Intelligence, Vol. 2534). ALT has been awarding the E. 432 pp. Englisch.

Hardcover. Condizione: new. Hardcover. 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. The central theme here is a model of prediction using expert advice, a general framework within which many related problems can be cast and discussed, including repeated game playing, adaptive data compression, sequential investment in the stock market, and sequential pattern analysis. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Hardcover. Condizione: new. Hardcover. 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. The central theme here is a model of prediction using expert advice, a general framework within which many related problems can be cast and discussed, including repeated game playing, adaptive data compression, sequential investment in the stock market, and sequential pattern analysis. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The central theme here is a model of prediction using expert advice, a general framework within which many related problems can be cast and discussed, including repeated game playing, adaptive data compression, sequential investment in the stock market, and.