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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)

Paper ID
7387
Venue
SIGMOD
Year
2026
Pagerank
4.1945683e-05
Overall Rank
10,078 | 29.89%
DOI
10.1145/3769791

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