EBSim: the algorithm for approximate single pair queries

Yinghao Zhao; Yu Liu

doi:10.1117/12.3034795

11 July 2024 EBSim: the algorithm for approximate single pair queries

Yinghao Zhao, Yu Liu

Proceedings Volume 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024); 1321018 (2024) https://doi.org/10.1117/12.3034795
Event: Third International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2024, Wuhan, China

Abstract

This paper proposes an algorithm strategy that utilizes the empirical Bernstein inequality to reduce the number of random walk samples in the single pair algorithm, thereby lowering the algorithm's theoretical complexity. An algorithm named EBSim is introduced, which combines the empirical Bernstein inequality by iteratively adjusting the number of samples, and it is proven to have strict error guarantees. The paper also provides a detailed analysis comparing this algorithm with the Monte Carlo algorithm, demonstrating that our algorithm achieves tighter confidence intervals, lower algorithm complexity, and higher efficiency in handling the same query problems. Experimental results show that, compared to the widely used Monte Carlo query algorithm, EBSim significantly improves algorithm efficiency while ensuring a given error tolerance.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yinghao Zhao and Yu Liu "EBSim: the algorithm for approximate single pair queries", Proc. SPIE 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024), 1321018 (11 July 2024); https://doi.org/10.1117/12.3034795

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