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Comparison of Rates of Linear and Neural Network Approximation
Como, Italy July 24-July 27
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.857848IEEE-INNS-ENNS International Joint Co ...
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Vera Kurková, Academy of Sciences of the Czech Republic
Marcello Sanguineti, University of Genoa
We develop some mathematical tools for comparison of rates of fixed versus variable basis function approximation. Using these tools, we describe sets of multivariable functions, for which lower bounds on worst-case errors in approximation by n -dimensional linear subspaces are larger than upper bounds on such errors in approximation by perceptron networks with n hidden units.
Index Terms:
linear and neural network approximation, Kolmogorov width, dimension-independent rates of approximation, perceptron networks
Citation:
Vera Kurková, Marcello Sanguineti, "Comparison of Rates of Linear and Neural Network Approximation," ijcnn, vol. 1, pp.1277, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 1, 2000
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