Journal of Systems Engineering and Electronics
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Tao Yang and Dongmei Fu
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Abstract:
Consider the efficiency of p-norm multiple kernel learning (MKL), which is extended to a semi-supervised learning (SSL) scenario by applying the manifold regularization technique. A manifold regularized p-norm multiple kernels model is constructed and applied to a semi-supervised classification task. Solutions are proposed for the case of p = 1, p > 1 and p = ∞, with an analysis of theorems and their proofs. In addition, experiments are conducted on several datasets using state-of-the-art methods to verify the efficiency of the proposed manifold regularized p-norm multiple kernels model in semi-supervised classification.
Tao Yang and Dongmei Fu. Semi-supervised classification based on p-norm multiple kernel learning with manifold regularization[J]. Journal of Systems Engineering and Electronics, doi: 10.21629/JSEE.2016.06.19.
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URL: https://www.jseepub.com/EN/10.21629/JSEE.2016.06.19
https://www.jseepub.com/EN/Y2016/V27/I6/1315