Open AccessWhich is better? Regularization in RKHS vs R^m on Reduced SVMs
Author(s) -
Shuisheng Zhou
Publication year - 2013
Publication title -
statistics optimization and information computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.297
H-Index - 12
eISSN - 2311-004X
pISSN - 2310-5070
DOI - 10.19139/27
Subject(s) - reproducing kernel hilbert space , representer theorem , support vector machine , mathematics , hilbert space , regularization (linguistics) , radial basis function kernel , norm (philosophy) , regularization perspectives on support vector machines , kernel method , kernel (algebra) , mathematical optimization , artificial intelligence , algorithm , computer science , discrete mathematics , pure mathematics , mathematical analysis , tikhonov regularization , inverse problem , law , political science
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