Articles with "multiple empirical" as a keyword



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Semi‐supervised multiple empirical kernel learning with pseudo empirical loss and similarity regularization

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Published in 2022 at "International Journal of Intelligent Systems"

DOI: 10.1002/int.22690

Abstract: Multiple empirical kernel learning (MEKL) is a scalable and efficient supervised algorithm based on labeled samples. However, there is still a huge amount of unlabeled samples in the real‐world application, which are not applicable for… read more here.

Keywords: labeled samples; empirical kernel; unlabeled samples; kernel learning ... See more keywords