On the Sample Complexity of Compressed Counting
Data Structures and Algorithms
2009-10-09 v1 Information Theory
math.IT
Abstract
Compressed Counting (CC), based on maximally skewed stable random projections, was recently proposed for estimating the p-th frequency moments of data streams. The case p->1 is extremely useful for estimating Shannon entropy of data streams. In this study, we provide a very simple algorithm based on the sample minimum estimator and prove a much improved sample complexity bound, compared to prior results.
Keywords
Cite
@article{arxiv.0910.1403,
title = {On the Sample Complexity of Compressed Counting},
author = {Ping Li},
journal= {arXiv preprint arXiv:0910.1403},
year = {2009}
}