Radial Basis Function Kernels
Radial Basis Function Kernels is a kernel function that belongs to the class of positive definite functions and is distinguished by its dependence on the Euclidean distance between input vectors, typically expressed as an exponentially decreasing function of the squared norm.
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Random Features for Large-Scale Kernel Machines
Ali Rahimi, Benjamin Recht · 2007 · 2.7K citations
Benchmarking Least Squares Support Vector Machine Classifiers
Tony Van Gestel, Johan A. K. Suykens, Bart Baesens et al. · Machine Learning · 2003 · 749 citations · Full text
On the training of radial basis function classifiers
M.T. Musavi, W. Ahmed, K.H. Chan et al. · Neural Networks · 1992 · 573 citations
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Uppsala University
Uppsala, Sweden
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33 publications
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Harbin Institute of Technology
Harbin, China
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42 publications
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City University of Hong Kong
Hong Kong, Hong Kong
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19 publications
1.5K citations

Southeast University
Nanjing, China
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34 publications
1.3K citations
National University of Singapore
Singapore, Singapore
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25 publications
2.4K citations
Amirkabir University of Technology
Tehran, Iran
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University of Malaya
Kuala Lumpur, Malaysia
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957 citations

Chinese Academy of Sciences
Beijing, China
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