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

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

HomePage Selected Books, Book Chapters. Underlying this need is the concept of “ connectionism”, which is concerned with the computational and learning capabilities of assemblies of simple processors, called artificial neural networks. Although this blog includes links to other Internet sites, it takes no responsibility for the content or information contained on those other sites, nor does it exert any editorial or other control over those other sites. Subjects: Neural and Evolutionary Computing (cs.NE); Information Theory (cs.IT); Learning (cs.LG); Differential Geometry (math.DG). Download free ebooks rapidshare, usenet,bittorrent. ALT 2011 - PDF Preprint Papers | Sciweavers . Neural Network Learning: Theoretical foundations, M. Noise," International Conference on Algorithmic Learning Theory. The artificial neural networks, which represent the electrical analogue of the biological nervous systems, are gaining importance for their increasing applications in supervised (parametric) learning problems. Artificial neural networks, a biologically inspired computing methodology, have the ability to learn by imitating the learning method used in the human brain. Ci-dessous donc la liste de mes bouquins favoris sur le sujet:A theory of learning an… Hébergé par OverBlog. Cite as: arXiv:1303.0818 [cs.NE]. Download free Neural Networks and Computational Complexity (Progress in Theoretical Computer Science) H. 'The book is a useful and readable mongraph. For beginners it is a nice introduction to the subject, for experts a valuable reference.