## Abstract The peeling of a __d__βdimensional set of points is usually performed with successive calls to a convex hull algorithm; the optimal worstβcase convex hull algorithm, known to have an __O__(__n__^Λ^ Log (n)) execution time, may give an __O__(__n__^Λ^__n__^Λ^ Log (n)) to peel all the set;
On Assessing the Performance of Randomized Algorithms
β Scribed by Sorana Froda
- Publisher
- Elsevier Science
- Year
- 2000
- Tongue
- English
- Weight
- 145 KB
- Volume
- 37
- Category
- Article
- ISSN
- 0196-6774
No coin nor oath required. For personal study only.
β¦ Synopsis
In this paper we study randomized algorithms with random input. We adapt to such algorithms the notion of probability of a false positive which is common in epidemiological studies. The probability of a false positive takes into account both the (controlled) error of the randomization and the randomness of the input, which needs to be modeled. We illustrate our idea on two classes of problems: primality testing and fingerprinting in strings transmission. Although in both cases the randomization has low error, in the first one the probability of a false positive is very low, while in the second one it is not. We end the paper with a discussion of randomness illustrated in a textbook example.
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