1997, ISBN: 9783540628583
This book constitutes the refereed proceedings of the Ninth European Conference on Machine Learning, ECML-97, held in Prague, Czech Republic, in April 1997. This volume presents 26 rev… Mehr…
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ISBN: 9783540628583
This book constitutes the refereed proceedings of the Ninth European Conference on Machine Learning, ECML-97, held in Prague, Czech Republic, in April 1997. This volume presents 26 revise… Mehr…
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Machine Learning: ECML'97: 9th European Conference on Machine Learning, Prague, Czech Republic, April 23 - 25, 1997, Proceedings (Lecture Notes in ... / Lecture Notes in Artificial Intelligence) - Taschenbuch
1997, ISBN: 9783540628583
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ISBN: 9783540628583
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1997, ISBN: 9783540628583
This book constitutes the refereed proceedings of the Ninth European Conference on Machine Learning, ECML-97, held in Prague, Czech Republic, in April 1997. This volume presents 26 rev… Mehr…
ISBN: 9783540628583
This book constitutes the refereed proceedings of the Ninth European Conference on Machine Learning, ECML-97, held in Prague, Czech Republic, in April 1997. This volume presents 26 revise… Mehr…
ISBN: 9783540628583
Paperback, [PU: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG], This book constitutes the refereed proceedings of the Ninth European Conference on Machine Learning, ECML-97, held in… Mehr…
Machine Learning: ECML'97: 9th European Conference on Machine Learning, Prague, Czech Republic, April 23 - 25, 1997, Proceedings (Lecture Notes in ... / Lecture Notes in Artificial Intelligence) - Taschenbuch
1997, ISBN: 9783540628583
Springer, 1997-05-16. Paperback. Very Good. Ex-library paperback in very nice condition with the usual markings and attachments., Springer, 1997-05-16, 3
ISBN: 9783540628583
*Machine Learning: ECML'97* - 9th European Conference on Machine Learning Prague Czech Republic April 23 - 25 1997 Proceedings. Auflage 1997 / Taschenbuch für 53.49 € / Aus dem Bereich: B… Mehr…
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Detailangaben zum Buch - Machine Learning: ECML'97
EAN (ISBN-13): 9783540628583
ISBN (ISBN-10): 3540628584
Taschenbuch
Erscheinungsjahr: 1997
Herausgeber: Springer Berlin Heidelberg
380 Seiten
Gewicht: 0,573 kg
Sprache: eng/Englisch
Buch in der Datenbank seit 2007-06-06T01:50:00+02:00 (Vienna)
Detailseite zuletzt geändert am 2024-02-12T13:09:54+01:00 (Vienna)
ISBN/EAN: 9783540628583
ISBN - alternative Schreibweisen:
3-540-62858-4, 978-3-540-62858-3
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: someren, widmer
Titel des Buches: czech republic, machine learning, republic com, european conference artificial intelligence, prague then and now, ecm
Daten vom Verlag:
Autor/in: Maarten van Someren; Gerhard Widmer
Titel: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; Machine Learning: ECML'97 - 9th European Conference on Machine Learning, Prague, Czech Republic, April 23 - 25, 1997, Proceedings
Verlag: Springer; Springer Berlin
366 Seiten
Erscheinungsjahr: 1997-04-09
Berlin; Heidelberg; DE
Sprache: Englisch
53,49 € (DE)
54,99 € (AT)
59,00 CHF (CH)
Available
XIV, 366 p.
BC; Hardcover, Softcover / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; Algorithmisches lernen; Entscheidungstheorie; Induktives Logisches Programmieren; Lernende Agenten; Maschinelles Lernen; algorithmic learning; classification; decision making; genetic programming; inductive logic programming; learning; logic; machine learning; programming; reinforcement learning; algorithm analysis and problem complexity; Artificial Intelligence; Algorithms; Algorithmen und Datenstrukturen; EA
Uncertain learning agents.- Constructing and sharing perceptual distinctions.- On prediction by data compression.- Induction of feature terms with INDIE.- Exploiting qualitative knowledge to enhance skill acquisition.- Integrated learning and planning based on truncating temporal differences.- ?-subsumption for structural matching.- Classification by Voting Feature Intervals.- Constructing intermediate concepts by decomposition of real functions.- Conditions for Occam's razor applicability and noise elimination.- Learning different types of new attributes by combining the neural network and iterative attribute construction.- Metrics on terms and clauses.- Learning when negative examples abound.- A model for generalization based on confirmatory induction.- Learning Linear Constraints in Inductive Logic Programming.- Finite-Element methods with local triangulation refinement for continuous reinforcement learning problems.- Inductive Genetic Programming with Decision Trees.- Parallel anddistributed search for structure in multivariate time series.- Compression-based pruning of decision lists.- Probabilistic Incremental Program Evolution: Stochastic search through program space.- NeuroLinear: A system for extracting oblique decision rules from neural networks.- Inducing and using decision rules in the GRG knowledge discovery system.- Learning and exploitation do not conflict under minimax optimality.- Model combination in the multiple-data-batches scenario.- Search-based class discretization.- Natural ideal operators in Inductive Logic Programming.- A case study in loyalty and satisfaction research.- Ibots learn genuine team solutions.- Global data analysis and the fragmentation problem in decision tree induction.- Case-based learning: Beyond classification of feature vectors.- Empirical learning of Natural Language Processing tasks.- Human-Agent Interaction and Machine Learning.- Learning in dynamically changing domains: Theory revision and context dependence issues.Weitere, andere Bücher, die diesem Buch sehr ähnlich sein könnten:
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