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Learning and Generalisation : With Applications to Neural Networks /

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Learning and Generalization provides a formal mathematical theory for addressing intuitive questions such as: How does a machine learn a new concept on the basis of examples? How can a neural network, after sufficient training, correctly predict the outcome of a previously unseen input? How much tra...

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Bibliographic Details
Main Author: Vidyasagar, M.
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: London : Springer London : Imprint : Springer, 2003.
Series:Communications and control engineering.
Subjects:
Engineering.
Computer Communication Networks.
Group theory.
System theory.
Distribution (Probability theory)
Engineering mathematics.
Electronic books.
Online Access:Connect to the full text of this electronic book

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