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ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
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On the Equivalence of the SMO and MDM Algorithms for SVM Training
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
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Neurocomputing
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ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II
Simple solvers for large quadratic programming tasks
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
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IEEE Transactions on Neural Networks
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IEEE Transactions on Neural Networks
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The nearest point problem (NPP), i.e., finding the closest points between two disjoint convex hulls, has two classical solutions, the Gilbert-Schlesinger-Kozinec (GSK) and Mitchell-Dem'yanov-Malozemov (MDM) algorithms. When the convex hulls do intersect, NPP has to be stated in terms of reduced convex hulls (RCHs), made up of convex pattern combinations whose coefficients are bound by a @m