• Corpus ID: 18769287

# Improving Monte Carlo randomized approximation schemes

@article{Huber2014ImprovingMC,
title={Improving Monte Carlo randomized approximation schemes},
author={Mark L. Huber},
journal={ArXiv},
year={2014},
volume={abs/1411.4074}
}
• M. Huber
• Published 14 November 2014
• Mathematics, Computer Science
• ArXiv
Consider a central problem in randomized approximation schemes that use a Monte Carlo approach. Given a sequence of independent, identically distributed random variables $X_1,X_2,\ldots$ with mean $\mu$ and standard deviation at most $c \mu$, where $c$ is a known constant, and $\epsilon,\delta > 0$, create an estimate $\hat \mu$ for $\mu$ such that $\text{P}(|\hat \mu - \mu| > \epsilon \mu) \leq \delta$. This technique has been used for building randomized approximation schemes for the volume…
1 Citations
• A. Montanaro
• Computer Science
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
• 2015
A quantum algorithm which can accelerate Monte Carlo methods in a very general setting, achieving a near-quadratic speedup over the best possible classical algorithm.

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