Articoli correlati a Computational Learning Theory and Natural Learning...
Computational Learning Theory and Natural Learning Systems: Intersections Between Theory and Experiment: 002 - Brossura
Sinossi
As with Volume I, this second volume represents a synthesis of issues in three historically distinct areas of learning research: computational learning theory, neural network research, and symbolic machine learning. While the first volume provided a forum for building a science of computational learning across fields, this volume attempts to define plausible areas of joint research: the contributions are concerned with finding constraints for theory while at the same time interpreting theoretic results in the context of experiments with actual learning systems. Subsequent volumes will focus on areas identified as research opportunities.
Computational learning theory, neural networks, and AI machine learning appear to be disparate fields; in fact they have the same goal: to build a machine or program that can learn from its environment. Accordingly, many of the papers in this volume deal with the problem of learning from examples. In particular, they are intended to encourage discussion between those trying to build learning algorithms (for instance, algorithms addressed by learning theoretic analyses are quite different from those used by neural network or machine-learning researchers) and those trying to analyze them.
The first section provides theoretical explanations for the learning systems addressed, the second section focuses on issues in model selection and inductive bias, the third section presents new learning algorithms, the fourth section explores the dynamics of learning in feedforward neural networks, and the final section focuses on the application of learning algorithms.
A Bradford Book
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Product Description
Book by None
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Risultati della ricerca per Computational Learning Theory and Natural Learning...
Foto dell'editore
Computational Learning Theory and Natural Learning Systems, Vol. II: Intersections between Theory and Experiment
Da: Wonder Book, Frederick, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
Condizione: Very Good. Very Good condition. Volume 2. A copy that may have a few cosmetic defects. May also contain a few markings such as an owner's name, short gifter's inscription or light stamp. Codice articolo K12O-00877
Quantità: 1 disponibili
Foto dell'editore
Computational Learning Theory and Natural Learning Systems, Vol. II: Intersections between Theory and Experiment
Da: Book House in Dinkytown, IOBA, Minneapolis, MN, U.S.A.
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: Very Good. Very good paperback. Spine is uncreased, binding tight and sturdy, text also very good. Ships from Dinkytown in Minneapolis, Minnesota. Codice articolo 165520
Quantità: 1 disponibili
Foto dell'editore
Computational Learning Theory and Natural Learning Systems Vol. 2 : Intersections Between Theory and Experiment
Da: PsychoBabel & Skoob Books, Didcot, Regno Unito
Valutazione del venditore 5 su 5 stelle
paperback. Condizione: Very Good. Condizione sovraccoperta: No Dust Jacket. Light shelfwear to cover edges but internally clean, tight and bright. Codice articolo 163778
Quantità: 1 disponibili
Foto dell'editore
Computational Learning Theory and Natural Learning Systems, Vol. II: Intersections between Theory and Experiment.
Da: Kloof Booksellers & Scientia Verlag, Amsterdam, Paesi Bassi
Valutazione del venditore 4 su 5 stelle
Condizione: as new. Cambridge, MA: The MIT Press, 1994. Paperback. 584 pp.- As with Volume I, this second volume represents a synthesis of issues in three historically distinct areas of learning research: computational learning theory, neural network research, and symbolic machine learning. While the first volume provided a forum for building a science of computational learning across fields, this volume attempts to define plausible areas of joint research: the contributions are concerned with finding constraints for theory while at the same time interpreting theoretic results in the context of experiments with actual learning systems. Subsequent volumes will focus on areas identified as research opportunities. Computational learning theory, neural networks, and AI machine learning appear to be disparate fields; in fact they have the same goal: to build a machine or program that can learn from its environment. Accordingly, many of the papers in this volume deal with the problem of learning from examples. In particular, they are intended to encourage discussion between those trying to build learning algorithms (for instance, algorithms addressed by learning theoretic analyses are quite different from those used by neural network or machine-learning researchers) and those trying to analyze them. English text. Condition : as new. Condition : as new copy. ISBN 9780262581332. Keywords : , Codice articolo 250226
Quantità: 1 disponibili
Foto dell'editore
Computational Lerning Theory and Natural Learning Systems. Volume II.Intersections between theory and experiment.
Editore:
London, The MIT Press, 1994., 1994
ISBN 10: 0262581337
ISBN 13: 9780262581332
Antico o usato
Brossura
Da: Antiquariat Hans Hammerstein OHG, München, Germania
Valutazione del venditore 4 su 5 stelle
origi.Broschur, kl.4°, 449 Seiten. Einband bestossen sonst guter Zustand. Codice articolo 41656
Quantità: 1 disponibili
Foto dell'editore
Computational Learning Theory and Natural Learning Systems: Intersections Between Theory and Experiment (A Bradford Book)
Da: Buchpark, Trebbin, Germania
Valutazione del venditore 5 su 5 stelle
Condizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher. Codice articolo 41382081/202
Quantità: 1 disponibili