Testing Distribution Identity Efficiently
Data Structures and Algorithms
2009-10-20 v1
Abstract
We consider the problem of testing distribution identity. Given a sequence of independent samples from an unknown distribution on a domain of size n, the goal is to check if the unknown distribution approximately equals a known distribution on the same domain. While Batu, Fortnow, Fischer, Kumar, Rubinfeld, and White (FOCS 2001) proved that the sample complexity of the problem is O~(sqrt(n) * poly(1/epsilon)), the running time of their tester is much higher: O(n) + O~(sqrt(n) * poly(1/epsilon)). We modify their tester to achieve a running time of O~(sqrt(n) * poly(1/epsilon)).
Keywords
Cite
@article{arxiv.0910.3243,
title = {Testing Distribution Identity Efficiently},
author = {Krzysztof Onak},
journal= {arXiv preprint arXiv:0910.3243},
year = {2009}
}
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4 pages