Efficient additive kernels via explicit feature maps
Large scale nonlinear support vector machines (SVMs) can be approximated by linear ones using a suitable feature map. The linear SVMs are in general much faster to learn and evaluate (test) than the original nonlinear SVMs. This work introduces explicit feature maps for the additive class of kernels...
| Hlavní autoři: | , |
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| Médium: | Journal article |
| Jazyk: | English |
| Vydáno: |
IEEE
2012
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