Parallel Rule Discovery from Large Datasets by Sampling
Summary: Parallel rule discovery for REEs across tables via multi-round sampling with alpha precision and beta recall guarantees. Deep Q-learning selects predicates for multi-variable rules; tableau boosts recall; parallelization yields 12.2x speedups at 10% sample. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Wenfei Fan (Beihang University; Shenzhen University; University of Edinburgh)
- 2. Ziyan Han (Beihang University)
- 3. Yaoshu Wang (Shenzhen University)
- 4. Min Xie (Shenzhen University)
BibTeX Citation
@inproceedings{fan_sigmod22,
title = {{Parallel Rule Discovery from Large Datasets by Sampling}},
author = {Fan, Wenfei and Han, Ziyan and Wang, Yaoshu and Xie, Min},
series = {{SIGMOD} '22},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3514221.3526165},
url = {https://dl.acm.org/doi/10.1145/3514221.3526165},
year = {2022}
}
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