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Neural Network Learning: Theoretical Foundations Martin Anthony, Peter L. Bartlett
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ALT 2011 - PDF Preprint Papers | Sciweavers . Learning theory (supervised/ unsupervised/ reinforcement learning) Knowledge based networks. There are so many different books on Neural Networks: Amazon's Neural Network. The network consists of two layers, .. 20120003110024) and the National Natural Science Foundation of China (Grant no. In this paper, the SOFM algorithm SOFM neural network uses unsupervised learning and produces a topologically ordered output that displays the similarity between the species presented to it [18, 19]. Because of its theoretical advantages, it is expected to apply Self-Organizing Feature Map to functional diversity analysis. Artificial Neural Networks Mathematical foundations of neural networks. Cheap This important work describes recent theoretical advances in the study of artificial neural networks. 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. Amazon.com: Neural Networks: Books Neural Network Learning: Theoretical Foundations by Martin Anthony and Peter L. Artificial neural networks, a biologically inspired computing methodology, have the ability to learn by imitating the learning method used in the human brain. Noise," International Conference on Algorithmic Learning Theory. HomePage Selected Books, Book Chapters.