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• W3165895868 abstract "Partial Rejection Sampling is an algorithmic approach to obtaining a perfect sample from a specified distribution. The objects to be sampled are assumed to be represented by a number of random variables. In contrast to classical rejection sampling, in which all variables are resampled until a feasible solution is found, partial rejection sampling aims at greater efficiency by resampling only a subset of variables that `go wrong'. Partial rejection sampling is closely related to Moser and Tardos' algorithmic version of the Lovasz Local Lemma, but with the additional requirement that a specified output distribution should be met. This article provides a largely self-contained account of the basic form of the algorithm and its analysis." @default.
• W3165895868 created "2021-06-22" @default.
• W3165895868 creator A5090122841 @default.
• W3165895868 date "2021-06-14" @default.
• W3165895868 modified "2023-09-27" @default.
• W3165895868 title "Fundamentals of Partial Rejection Sampling." @default.
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