@article{393fb1c2a99e41de8c5d4ec93ceb23b0,
title = "Lower bounds for sampling algorithms for estimating the average",
abstract = "We show lower bounds on the number of sample points and on the number of coin tosses used by general sampling algorithms for estimating the average value of functions over a large domain. The bounds depend on the desired precision and on the error probability of the estimate. Our lower bounds match upper bounds established by known algorithms, up to a multiplicative constant. Furthermore, we give a non-constructive proof of existence of an algorithm that improves the known upper bounds by a constant factor.",
keywords = "Estimating, Lower bounds, Randomness, Sampling, Theory of computation",
author = "Ran Canetti and Guy Even and Oded Goldreich",
note = "Funding Information: * Corresponding author. Email:
[email protected]. {\textquoteleft} Supported by grants No. 89-003 12 and 92-00226 from the United States-Israel",
year = "1995",
month = jan,
day = "13",
doi = "10.1016/0020-0190(94)00171-T",
language = "אנגלית",
volume = "53",
pages = "17--25",
journal = "Information Processing Letters",
issn = "0020-0190",
publisher = "Elsevier B.V.",
number = "1",
}