Indefinite Kernel Network with lq‐Norm Regularization

Zhongfeng Qu and Hongwei Sun

Discrete Dynamics in Nature and Society, 2016, vol. 2016, issue 1

Abstract: We study the asymptotical properties of indefinite kernel network with lq‐norm regularization. The framework under investigation is different from classical kernel learning. Positive semidefiniteness is not required by the kernel function. By a new step stone technique, without any interior cone condition for input space X and Lτ condition for the probability measure ρX, satisfied error bounds and learning rates are deduced.

Date: 2016
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https://doi.org/10.1155/2016/6516258

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Persistent link: https://EconPapers.repec.org/RePEc:wly:jnddns:v:2016:y:2016:i:1:n:6516258

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