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- W4310630112 abstract "We analyze the hit-and-run algorithm for sampling uniformly from an isotropic convex body $K$ in $n$ dimensions. We show that the algorithm mixes in time $tilde{O}(n^2/ psi_n^2)$, where $psi_n$ is the smallest isoperimetric constant for any isotropic logconcave distribution, also known as the Kannan-Lovasz-Simonovits (KLS) constant. Our bound improves upon previous bounds of the form $tilde{O}(n^2 R^2/r^2)$, which depend on the ratio $R/r$ of the radii of the circumscribed and inscribed balls of $K$, gaining a factor of $n$ in the case of isotropic convex bodies. Consequently, our result gives a mixing time estimate for the hit-and-run which matches the state-of-the-art bounds for the ball walk. Our main proof technique is based on an annealing of localization schemes introduced in Chen and Eldan (2022), which allows us to reduce the problem to the analysis of the mixing time on truncated Gaussian distributions." @default.
- W4310630112 created "2022-12-13" @default.
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- W4310630112 date "2022-12-01" @default.
- W4310630112 modified "2023-10-16" @default.
- W4310630112 title "Hit-and-run mixing via localization schemes" @default.
- W4310630112 doi "https://doi.org/10.48550/arxiv.2212.00297" @default.
- W4310630112 hasPublicationYear "2022" @default.
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