Editor thomas petsche (3 résultats)
- Couverture souple
Vendeur : Kloof Booksellers & Scientia Verlag, Amsterdam, Pays-BasKloof Booksellers & Scientia Verlag
Contacter le vendeurVendeur avec une évaluation de 4 étoilesEtat: Occasion - Comme neuf
EUR 15,95
EUR 30,00 expéditionExpédition depuis Pays-Bas vers Etats-UnisQuantité disponible : 1 disponible(s)
Etat : as new. Cambridge, MA: The MIT Press, 1995. Paperback. 405 pp.- This is the third in a series of edited volumes exploring the evolving landscape of learning systems research which spans theory and experiment, symbols and signals. It continues the exploration of the synthesis of the machine learning subdisciplines begun in… volumes I and II. The nineteen contributions cover learning theory, empirical comparisons of learning algorithms, the use of prior knowledge, probabilistic concepts, and the effect of variations over time in the concepts and feedback from the environment. The goal of this series is to explore the intersection of three historically distinct areas of learning research: computational learning theory, neural networks andAI machine learning. Although each field has its own conferences, journals, language, research, results, and directions, there is a growing intersection and effort to bring these fields into closer coordination. English text. Condition : as new. Condition : as new copy. ISBN 9780262660969. Keywords : .
- Couverture souple
Vendeur : Kloof Booksellers & Scientia Verlag, Amsterdam, Pays-BasKloof Booksellers & Scientia Verlag
Contacter le vendeurVendeur avec une évaluation de 4 étoilesEtat: Occasion - Comme neuf
EUR 15,95
EUR 30,00 expéditionExpédition depuis Pays-Bas vers Etats-UnisQuantité disponible : 1 disponible(s)
Etat : 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 : .
Computational Learning Theory and Natural Learning Systems: Making Learning Systems Practical: Vol 4
Greiner, Russell (Editor)/ Petsche, Thomas (Editor)/ Hanson, Stephen Jose (Editor)
- Couverture souple
Vendeur : Revaluation Books, Exeter, Royaume-UniRevaluation Books
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 85,71
EUR 14,66 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 1 disponible(s)
Paperback. Etat : Brand New. 407 pages. 9.25x7.25x1.00 inches. In Stock.
