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#logconcave

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papersTODAY 04:00 UTC

Thin-shell stability yields faster logconcave sampling from a cold start

A new arXiv paper proves that logconcave probability measures lying along the Gaussian cooling path satisfy a thin-shell stability property, extending the classical thin-shell theorem. This stability result translates into better complexity bounds for the core task of drawing samples from an arbitrary logconcave distribution, including when the process begins from a cold start rather than a warm one. The work sits in the theory of Markov chain Monte Carlo and sampling algorithm analysis.

sampling/logconcave/theory/optimization