Better Bounds for Frequency Moments in Random-Order Streams
Data Structures and Algorithms
2008-08-19 v1
Abstract
Estimating frequency moments of data streams is a very well studied problem and tight bounds are known on the amount of space that is necessary and sufficient when the stream is adversarially ordered. Recently, motivated by various practical considerations and applications in learning and statistics, there has been growing interest into studying streams that are randomly ordered. In the paper we improve the previous lower bounds on the space required to estimate the frequency moments of a randomly ordered streams.
Cite
@article{arxiv.0808.2222,
title = {Better Bounds for Frequency Moments in Random-Order Streams},
author = {Alexandr Andoni and Andrew McGregor and Krzysztof Onak and Rina Panigrahy},
journal= {arXiv preprint arXiv:0808.2222},
year = {2008}
}
Comments
4 pages