Before revision: We introduce kernel thinning, a simple algorithm for generating better-than-Monte-Carlo approximations to distributions \mathbb{P a suitable reproducing kernel k , and O(n^2) time, kernel thinning returns \sqrt{n in the associated reproducing kernel Hilbert space.
After revision: We introduce kernel thinning, a new procedure for compressing a distribution \mathbb{P a suitable reproducing kernel k , and O(n^2) time, kernel thinning returns \sqrt{n in the associated reproducing kernel Hilbert space.