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For many probability distributions of interest, it is quite difficult to obtain samples efficiently. Often, Markov chains are employed to obtain approximately random samples from these distributions. The primary drawback to traditional Markov chain methods is that the mixing time of the chain is usually unknown, which makes it impossible to determine how close the output samples are to having the target distribution. Here we present a new protocol, the randomness recycler (RR), that overcomesdoi:10.1109/sfcs.2000.892138 dblp:conf/focs/FillH00 fatcat:gtwq7oe3qndbdd4jpb7wguekby