Journal
NEUROCOMPUTING
Volume 90, Issue -, Pages 46-58Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2011.12.036
Keywords
Multiple kernel learning; Inductive semi-supervised learning; Transductive SVM; DC programming; BCI application
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We investigate the benefit of combining both cluster assumption and manifold assumption underlying most of the semi-supervised algorithms using the flexibility and the efficiency of multiple kernel learning. The multiple kernel version of Transductive SVM (a cluster assumption based approach) is proposed and it is solved based on DC (Difference of Convex functions) programming. Promising results on benchmark data sets and the BCI data analysis suggest and support the effectiveness of proposed work. (C) 2012 Elsevier B.V. All rights reserved.
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