2023
DOI: 10.1109/access.2023.3331685
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Sequential Minimal Optimization Algorithm for One-Class Support Vector Machines With Privileged Information

Andrey Lange,
Dmitry Smolyakov,
Evgeny Burnaev

Abstract: One of the powerful techniques in data modeling is accounting for features that are available at the training stage, but are not available when the trained model is used to classify or predict test data -Learning Using Privileged Information paradigm (LUPI, Vapnik and Vashist [1]). Sequential Minimal Optimization (SMO) method has been already developed for supervised Support Vector Machines (SVM) in Platt [2] and Keerthi et al. [3], for unsupervised (one-class) SVM in Schölkopf et al. [4], and for SVM with pri… Show more

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