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Debiased Distribution Compression
April 19, 2024, 4:42 a.m. | Lingxiao Li, Raaz Dwivedi, Lester Mackey
cs.LG updates on arXiv.org arxiv.org
Abstract: Modern compression methods can summarize a target distribution $\mathbb{P}$ more succinctly than i.i.d. sampling but require access to a low-bias input sequence like a Markov chain converging quickly to $\mathbb{P}$. We introduce a new suite of compression methods suitable for compression with biased input sequences. Given $n$ points targeting the wrong distribution and quadratic time, Stein Kernel Thinning (SKT) returns $\sqrt{n}$ equal-weighted points with $\widetilde{O}(n^{-1/2})$ maximum mean discrepancy (MMD) to $\mathbb {P}$. For larger-scale compression …
abstract access arxiv bias compression cs.lg distribution low markov modern sampling stat.co stat.me stat.ml targeting type
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