Signed random Fourier features for fast density estimation with indefinite kernels
The signed random Fourier features (SRFF) technique is introduced, a generalization of RFF compatible with indefinite kernels whose inverse Fourier transform is absolutely integrable and speed up KDE in the case of multivariate compact kernels, which are generally not positive definite.
Wangjiang Xie, N. Langrené, Wen Chen
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