# Robust estimation of the mean with bounded relative standard deviation

@article{Huber2018RobustEO, title={Robust estimation of the mean with bounded relative standard deviation}, author={Mark Huber}, journal={arXiv: Computation}, year={2018} }

Many randomized approximation algorithms operate by giving a procedure for simulating a random variable $X$ which has mean $\mu$ equal to the target answer, and a relative standard deviation bounded above by a known constant $c$. Examples of this type of algorithm includes methods for approximating the number of satisfying assignments to 2-SAT or DNF, the volume of a convex body, and the partition function of a Gibbs distribution. Because the answer is usually exponentially large in the problem… CONTINUE READING

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