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• W2128135822 abstract "Relational discriminant analysis is based on a similarity matrix of the training set. It is able to construct reliable nonlinear discriminants in infinite dimensional feature spaces based on small training sets. This technique has a large sample size problem as the size of the similarity matrix equals the square of the number of objects in the training set. We discuss and initially evaluate a solution that drastically decreases training times and memory demands." @default.
• W2128135822 created "2016-06-24" @default.
• W2128135822 creator A5037908027 @default.
• W2128135822 date "2002-11-27" @default.
• W2128135822 modified "2023-09-23" @default.
• W2128135822 title "Relational discriminant analysis and its large sample size problem" @default.
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• W2128135822 doi "https://doi.org/10.1109/icpr.1998.711176" @default.
• W2128135822 hasPublicationYear "2002" @default.
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