Items related to Computational Learning Theory & Natural Learning...
Computational Learning Theory & Natural Learning Systems V 1 Constraints & Prospects: Constraints and Prospects: Volume 1 (A Bradford Book) - Softcover
Synopsis
These original contributions converge on an exciting and fruitful intersection of three historically distinct areas of learning research: computational learning theory, neural networks, and symbolic machine learning. Bridging theory and practice, computer science and psychology, they consider general issues in learning systems that could provide constraints for theory and at the same time interpret theoretical results in the context of experiments with actual learning systems.
In all, nineteen chapters address questions such as, What is a natural system? How should learning systems gain from prior knowledge? If prior knowledge is important, how can we quantify how important? What makes a learning problem hard? How are neural networks and symbolic machine learning approaches similar? Is there a fundamental difference in the kind of task a neural network can easily solve as opposed to those a symbolic algorithm can easily solve?
Stephen J. Hanson heads the Learning Systems Department at Siemens Corporate Research and is a Visiting Member of the Research Staff and Research Collaborator at the Cognitive Science Laboratory at Princeton University. George A. Drastal is Senior Research Scientist at Siemens Corporate Research. Ronald J. Rivest is Professor of Computer Science and Associate Director of the Laboratory for Computer Science at the Massachusetts Institute of Technology.
"synopsis" may belong to another edition of this title.
About the Authors
George A. Drastal is Senior Research Scientist at Siemens Corporate Research.
Stephen José Hanson is Professor of Psychology (Newark Campus) and Member of the Cognitive Science Center (New Brunswick Campus) at Rutgers University.
Ronald L. Rivest is Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology.
"About this title" may belong to another edition of this title.
Buy New
View this item
£ 39.03
£ 21.86 shipping from U.S.A. to United Kingdom
Destination, rates & speedsSearch results for Computational Learning Theory & Natural Learning...
Stock Image
Computational Learning Theory and Natural Learning Systems, Volume 1: Constraints and Prospects
Published by
The MIT Press - a Bradford book 1st edn, 1994
ISBN 10: 0262581264
ISBN 13: 9780262581264
Used
Soft cover
First Edition
Seller: G. & J. CHESTERS, TAMWORTH, United Kingdom
Seller rating 5 out of 5 stars
Soft cover. Condition: Very Good. 1st Edition. 566 pages, a VG paperback (does have a small crease across top corner of the back cover) [0262581264]. Seller Inventory # 74398
Quantity: 1 available
Stock Image
Computational Learning Theory and Natural Learning Systems, Vol. I: Constraints and Prospects.
Seller: Kloof Booksellers & Scientia Verlag, Amsterdam, Netherlands
Seller rating 4 out of 5 stars
Condition: as new. Cambridge, MA: The MIT Press, 1994. Paperback. 500 pp.- These original contributions converge on an exciting and fruitful intersection of three historically distinct areas of learning research: computational learning theory, neural networks, and symbolic machine learning. Bridging theory and practice, computer science and psychology, they consider general issues in learning systems that could provide constraints for theory and at the same time interpret theoretical results in the context of experiments with actual learning systems. In all, nineteen chapters address questions such as, What is a natural system? How should learning systems gain from prior knowledge? If prior knowledge is important, how can we quantify how important? What makes a learning problem hard? How are neural networks and symbolic machine learning approaches similar? Is there a fundamental difference in the kind of task a neural network can easily solve as opposed to those a symbolic algorithm can easily solve? English text. Condition : as new. Condition : as new copy. ISBN 9780262581264. Keywords : , Seller Inventory # 250676
Quantity: 1 available
Stock Image
Computational Learning Theory and Natural Learning Systems, Vol. I: Constraints and Prospects
Seller: Ammareal, Morangis, France
Seller rating 5 out of 5 stars
Softcover. Condition: Très bon. Ancien livre de bibliothèque. Edition 1994. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 1994. Ammareal gives back up to 15% of this item's net price to charity organizations. Seller Inventory # F-924-466
Quantity: 1 available
Stock Image
Computational Learning Theory and Natural Learning Systems: Constraints and Prospects (A Bradford Book)
Seller: Buchpark, Trebbin, Germany
Seller rating 5 out of 5 stars
Condition: Sehr gut. Zustand: Sehr gut | Seiten: 577 | Sprache: Englisch | Produktart: Bücher. Seller Inventory # 41380194/202
Quantity: 1 available
Stock Image
Computational Learning Theory and Natural Learning Systems, Vol. I: Constraints and Prospects
Seller: BOOKWEST, Phoenix, AZ, U.S.A.
Seller rating 2 out of 5 stars
Soft cover. Condition: New. US SELLER SHIPS FAST FROM USA. Seller Inventory # MA-144A1-0262581264
Quantity: 1 available
Stock Image
Computational Learning Theory and Natural Learning Systems, Vol. I: Constraints and Prospects
Seller: Mispah books, Redhill, SURRE, United Kingdom
Seller rating 4 out of 5 stars
paperback. Condition: Very Good. Very Good. book. Seller Inventory # ERICA82902625812645
Quantity: 1 available