Unsupervised Learning: Foundations of Neural Computation by Geoffrey Hinton

Unsupervised Learning: Foundations of Neural Computation

EditorGeoffrey Hinton, Terrence J. Sejnowski

Paperback | May 24, 1999

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Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computationcollects, by topic, the most significant papers that have appeared in the journal over the past nine years.This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.

About The Author

Geoffrey Hinton is Professor of Computer Science at the University of Toronto.
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Title:Unsupervised Learning: Foundations of Neural ComputationFormat:PaperbackDimensions:414 pages, 9 × 6 × 0.9 inPublished:May 24, 1999Publisher:The MIT PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:026258168X

ISBN - 13:9780262581684

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An edition of the journal Foundations of Neural Computations, Unsupervised Learning and Map Foundation focuses on neural network learning algorithms that don’t require an explicit teacher. The algorithms offer an understanding of the growth of the cerebral cortex and implicit learning in human beings. It also provides insight into engineers’ work in the area of computer vision and speech recognition.