Abstract
We consider the problem of computing with many coins of unknown bias. We are given access to samples of n coins with unknown biases and are asked to sample from a coin with bias for a given function . We give a complete characterization of the functions f for which this is possible. As a consequence, we show how to extend various combinatorial sampling procedures (most notably, the classic Sampford sampling for k-subsets) to the boundary of the hypercube.
Citation
Renato Paes Leme. Jon Schneider. "Multiparameter Bernoulli factories." Ann. Appl. Probab. 33 (5) 3987 - 4007, October 2023. https://doi.org/10.1214/22-AAP1913
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