Optimal testing of discrete distributions with high probability

@article{Diakonikolas2020OptimalTO,
title={Optimal testing of discrete distributions with high probability},
author={Ilias Diakonikolas and Themis Gouleakis and Daniel M. Kane and John Peebles and Eric Price},
journal={Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing},
year={2020}
}
• Ilias Diakonikolas, +2 authors Eric Price
• Published 2020
• Computer Science, Mathematics
• Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing
We study the problem of testing discrete distributions with a focus on the high probability regime. Specifically, given samples from one or more discrete distributions, a property P, and parameters 0< є, δ <1, we want to distinguish with probability at least 1−δ whether these distributions satisfy P or are є-far from P in total variation distance. Most prior work in distribution testing studied the constant confidence case (corresponding to δ = Ω(1)), and provided sample-optimal testers for a… Expand
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