Estimating Biclique Counts with Accuracy Guarantees
Summary: First approximation algorithm for (p,q)-biclique counting with formal error and failure-probability guarantees, using an edge-oriented sampling framework (BC-Shadow) that refines the sample space to increase biclique density and cut sample complexity. Introduces zstar, a one-to-one sampling structure, and an adaptive sampling rule; provides provable accuracy/runtime bounds and scalable empirical validation on large real graphs. (summarized by gpt-5-mini on Feb 11 2026)
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Authors
- 1. Rashmika Gamage (University of Sydney)
- 2. Lijun Chang (University of Sydney)
BibTeX Citation
@inproceedings{gamage_sigmod26,
title = {{Estimating Biclique Counts with Accuracy Guarantees}},
author = {Gamage, Rashmika and Chang, Lijun},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3769791},
url = {https://dl.acm.org/doi/10.1145/3769791},
year = {2026}
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