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Double Sparsity Kernel Learning with Automatic Variable Selection and Data Extraction

Learning in the Reproducing Kernel Hilbert Space (RKHS) has been widely used in many scientific disciplines. Because a RKHS can be very flexible, it is common to impose a regularization term in the optimization to prevent overfitting. Standard RKHS learning employs the squared norm penalty of the le...

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Detalhes bibliográficos
Publicado no:Stat Interface
Main Authors: Chen, Jingxiang, Zhang, Chong, Kosorok, Michael R., Liu, Yufeng
Formato: Artigo
Idioma:Inglês
Publicado em: 2018
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC6168218/
https://ncbi.nlm.nih.gov/pubmed/30294406
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.4310/SII.2018.v11.n3.a1
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