Efficient additive kernels via explicit feature maps

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...

书目详细资料
Main Authors:	Vedaldi, A, Zisserman, A
格式:	Journal article
语言:	English
出版:	IEEE 2012

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