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Approximations based on random Fourier features have recently emerged as an efficient and formally consistent methodology to design large-scale kernel machines [24]. By expressing the kernel as a Fourier expansion, features are generated based on a finite set of random basis projections , sampled from the Fourier transform of the kernel, with inner products(More)
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