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arXiv · 2109.06366

A Dyadic Simulation Approach to Efficient Range-Summability

Jingfan Meng·Huayi Wang·Jun Xu·Mitsunori Ogihara
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Abstract

Efficient range-summability (ERS) of a long list of random variables is a fundamental algorithmic problem that has applications to three important database applications, namely, data stream processing, space-efficient histogram maintenance (SEHM), and approximate nearest neighbor searches (ANNS). In this work, we propose a novel dyadic simulation framework and develop three novel ERS solutions, namely Gaussian-dyadic simulation tree (DST), Cauchy-DST and Random Walk-DST, using it. We also propose novel rejection sampling techniques to make these solutions computationally efficient. Furthermore, we develop a novel k-wise independence theory that allows our ERS solutions to have both high computational efficiencies and strong provable independence guarantees.

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BibTeXRIS

Jingfan Meng, Huayi Wang, Jun Xu, Mitsunori Ogihara. 2021-09-13. A Dyadic Simulation Approach to Efficient Range-Summability. https://arxiv.org/abs/2109.06366

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