Lower Bounds for Sampling Algorithms for Estimating the Average
نویسندگان
چکیده
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 mul-tiplicative constant. Furthermore, we give a non-constructive proof of existence of an algorithm that improves the known upper bounds by a constant factor.
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ورودعنوان ژورنال:
- Inf. Process. Lett.
دوره 53 شماره
صفحات -
تاریخ انتشار 1995