Speeding up Support Vector Machines - Probabilistic versus Nearest Neighbour Methods for Condensing Training Data - researchr publication related

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Moïri Gamboni, Abhijai Garg, Oleg Grishin, Seung Man Oh, Francis Sowani, Anthony Spalvieri-Kruse, Godfried T. Toussaint, Lingliang Zhang. Speeding up Support Vector Machines - Probabilistic versus Nearest Neighbour Methods for Condensing Training Data. In Maria De Marsico, Antoine Tabbone, Ana L. N. Fred, editors, ICPRAM 2014 - Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods, ESEO, Angers, Loire Valley, France, 6-8 March, 2014. pages 364-371, SciTePress, 2014. [doi]

The following publications are possibly variants of this publication:

An Empirical Comparison of Support Vector Machines Versus Nearest Neighbour Methods for Machine Learning ApplicationsMoïri Gamboni, Abhijai Garg, Oleg Grishin, Seung Man Oh, Francis Sowani, Anthony Spalvieri-Kruse, Godfried T. Toussaint, Lingliang Zhang. icpram 2015: 110-129 [doi]

Fast instance selection for speeding up support vector machinesJingnian Chen, Caiming Zhang, Xiaoping Xue, Cheng-Lin Liu. kbs, 45:1-7, 2013. [doi]

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