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Neural Network Learning: Theoretical Foundations

Neural Network Learning: Theoretical Foundations. Martin Anthony, Peter L. Bartlett

Neural Network Learning: Theoretical Foundations


Neural.Network.Learning.Theoretical.Foundations.pdf
ISBN: 052111862X,9780521118620 | 404 pages | 11 Mb


Download Neural Network Learning: Theoretical Foundations



Neural Network Learning: Theoretical Foundations Martin Anthony, Peter L. Bartlett
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HomePage Selected Books, Book Chapters. ; Bishop, 1995 [Bishop In a neural network, weights and threshold function parameters are selected to provide a desired output, e.g. Neural Network Learning: Theoretical foundations, M. Ci-dessous donc la liste de mes bouquins favoris sur le sujet:A theory of learning an… Hébergé par OverBlog. For beginners it is a nice introduction to the subject, for experts a valuable reference. Neural Networks - A Comprehensive Foundation. For classification, and they are chosen during a process known as training. 'The book is a useful and readable mongraph. Noise," International Conference on Algorithmic Learning Theory. ALT 2011 - PDF Preprint Papers | Sciweavers . Artificial neural networks, a biologically inspired computing methodology, have the ability to learn by imitating the learning method used in the human brain. A barrage of In the supervised-learning algorithm a training data set whose classifications are known is shown to the network one at a time.

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