On Practical Algorithms for Entropy Estimation and the Improved Sample Complexity of Compressed Counting

Details On Practical Algorithms for Entropy Estimation and the Improved Sample Complexity of Compressed Counting On Practical Algorithms for Entropy Estimation and the Improved Sample Complexity of Compressed Counting

2010-04-21

arxiv.org/abs/1004.3782v1

Computer Science

Data Structures and Algorithms

Scientific paper

Estimating the p-th frequency moment of data stream is a very heavily studied problem. The problem is actually trivial when p = 1, assuming the strict Turnstile model. The sample complexity of our proposed algorithm is essentially O(1) near p=1. This is a very large improvement over the previously believed O(1/eps^2) bound. The proposed algorithm makes the long-standing problem of entropy estimation an easy task, as verified by the experiments included in the appendix.

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