![Computational learning theory / Artificial neural networks / Machine learning / Computational statistics / Learning / VC dimension / Sample complexity / Probably approximately correct learning / Backpropagation / Perceptron / Vladimir Vapnik / Radial basis function network Computational learning theory / Artificial neural networks / Machine learning / Computational statistics / Learning / VC dimension / Sample complexity / Probably approximately correct learning / Backpropagation / Perceptron / Vladimir Vapnik / Radial basis function network](https://www.pdfsearch.io/img/feafe06d868bfbaa7de02903f2534ea4.jpg) Date: 2000-04-03 14:19:07Computational learning theory Artificial neural networks Machine learning Computational statistics Learning VC dimension Sample complexity Probably approximately correct learning Backpropagation Perceptron Vladimir Vapnik Radial basis function network | | PAC Learning and Artificial Neural Networks Martin Anthony and Norman Biggs Department of Mathematics, London School of Economics and Political Science (University of London), Houghton St., London WC2A 2AE, United Kingdo
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