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- W2061713275 abstract "The reproducing kernel Hilbert space construction is a bijection or transform theory which associates a positive definite kernel with a Hilbert space of functions. Recently, reproducing kernel Hilbert space (RKHS) has come wildly alive in the pattern recognition and machine learning community. In this paper, we propose a novel method named multiple kernel learning with reproducing property (MKLRP) to achieve some classification tasks. The MKLRP consists of two major steps. First, we find the basic solution of a generalized differential operator by delta function, and prove this basic solution is a new specific reproducing kernel called H 2 -reproducing kernel (HRK) in RKHS. Second, in RKHS, we prove that the HRK satisfies the condition of Mercer kernel. Furthermore, a novel specific multiple kernel learning (MKL) called MKLRP, which is based on reproducing kernel is proposed. We perform an extensive experimental evaluation on synthetic and real-world data, which shows the effectiveness of the proposed approach." @default.
- W2061713275 created "2016-06-24" @default.
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- W2061713275 date "2015-03-01" @default.
- W2061713275 modified "2023-09-25" @default.
- W2061713275 title "An efficient multiple kernel learning in reproducing kernel Hilbert spaces (RKHS)" @default.
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- W2061713275 doi "https://doi.org/10.1142/s0219691315500083" @default.
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