Double sparsity kernel learning with automatic variable selection and data extraction
نویسندگان
چکیده
منابع مشابه
Double Sparsity Kernel Learning with Automatic Variable Selection and Data Extraction
Learning with Reproducing Kernel Hilbert Spaces (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 learning function. Despite its success, many challenges remain. In particular, one cannot directly u...
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ژورنال
عنوان ژورنال: Statistics and Its Interface
سال: 2018
ISSN: 1938-7989,1938-7997
DOI: 10.4310/sii.2018.v11.n3.a1