no code implementations • NeurIPS 2018 • Md Enayat Ullah, Poorya Mianjy, Teodor Vanislavov Marinov, Raman Arora
We study the statistical and computational aspects of kernel principal component analysis using random Fourier features and show that under mild assumptions, $O(\sqrt{n} \log n)$ features suffices to achieve $O(1/\epsilon^2)$ sample complexity.
