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The Tractability Landscape of Sampling with Inexact Scores

2026/07/21 by Anming Gu, Kevin Tian, Hubert Yang +1
#stat.ML #cs.LG #math.ST #stat.TH

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Abstract

We provide a simple and tight characterization of the types of inexact score oracle access that permit sampling with vanishing total variation bias, for a standard, well-behaved target family. Our main result shows that any weaker error than the sub-Gaussian assumption used by [YW26] rules out the tractability of unbiased sampling. This strengthens the conclusion of [CCSW26] to be algorithm-agnostic, and to hold for a wider range of error assumptions.

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