In a recent video presentation when Vikas Sindhwani talked about Random Embeddings, Matrix-valued Kernels and Deep Learning, he mentioned that instead of using purely random features we ought to be looking at Quasi-Monte Carlo series of numbers [1]. Sebastien Bubeck just hosted a blog post pn the subject entitled Beating Monte Carlo a guest post by Sasho Nikolov which linked to the pdf version of this book by Bernard Chazelle on the Discrepancy Method.
[1] Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels Jiyan Yang, Vikas Sindhwani, Haim Avron, Michael Mahoney
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