IEEE - Institute of Electrical and Electronics Engineers, Inc. - Tikhonov-based Regularization of a Global Optimum Approach of One-layer Neural Networks with Fixed Transfer Function by Convex Optimization

Proceedings of 2005 International Conference on Neural Networks and Brain

Author(s): Dik Kin Wong ; M.P. Guimaraes ; E.T. Uy ; P. Suppes
Publisher: IEEE - Institute of Electrical and Electronics Engineers, Inc.
Publication Date: 1 January 2005
Conference Location: Beijing, China
Conference Date: 13 October 2005
Volume: 3
Page(s): 1,564 - 1,567
ISBN (Paper): 0-7803-9422-4
DOI: 10.1109/ICNNB.2005.1614930
Regular:

Regularization is useful for extending learning models to be effective for classifications. Given the success of regularized-perceptron-based (one-layer neural network) methods, a similar... View More

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