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Neural Network Learning: Theoretical Foundations
Neural Network Learning: Theoretical Foundations

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

Neural Network Learning: Theoretical Foundations



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Neural Network Learning: Theoretical Foundations Martin Anthony, Peter L. Bartlett ebook
Page: 404
ISBN: 052111862X, 9780521118620
Publisher:
Format: pdf


Artificial Neural Networks Mathematical foundations of neural networks. 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. This important work describes recent theoretical advances in the study of artificial neural networks. Cite as: arXiv:1303.0818 [cs.NE]. Learning theory (supervised/ unsupervised/ reinforcement learning) Knowledge based networks. There are so many different books on Neural Networks: Amazon's Neural Network. ; Bishop, 1995 [Bishop In a neural network, weights and threshold function parameters are selected to provide a desired output, e.g. Amazon.com: Neural Networks: Books Neural Network Learning: Theoretical Foundations by Martin Anthony and Peter L. Neural Networks - A Comprehensive Foundation. Subjects: Neural and Evolutionary Computing (cs.NE); Information Theory (cs.IT); Learning (cs.LG); Differential Geometry (math.DG). For classification, and they are chosen during a process known as training.

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