Efficient k-Clique Count Estimation with Accuracy Guarantee
Summary: SR-kCCE pre-determines s, the number of uniformly sampled k-cliques required to meet a provable accuracy guarantee and to estimate sampling time. It stops refining the superset sample space when elapsed time ≈ estimated sampling time, balancing construction vs sampling and enabling efficient u.a.r. sampling. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Lijun Chang (University of Sydney)
- 2. Rashmika Gamage (University of Sydney)
- 3. Jeffrey Xu Yu (Chinese University of Hong Kong)
BibTeX Citation
@article{chang_vldb24,
title = {{Efficient k-Clique Count Estimation with Accuracy Guarantee}},
author = {Chang, Lijun and Gamage, Rashmika and Yu, Jeffrey Xu},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {11},
pages = {3707--3719},
doi = {10.14778/3681954.3682032},
url = {https://doi.org/10.14778/3681954.3682032},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,548 | Maximum Defective Clique Computation: Improved Time Complexities and Practical Performance | 2025 | VLDB | 5.2528121e-05 |
| 10,365 | Efficient Defective Clique Enumeration and Search with Worst-Case Optimal Search Space | 2026 | SIGMOD | 5.093636e-05 |
| 10,369 | Estimating Biclique Counts with Accuracy Guarantees | 2026 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,307 | KClist++: A Simple Algorithm for Finding k-Clique Densest Subgraphs in Large Graphs | 2020 | VLDB | 0.00011232263 |
| 3,613 | Scaling Up k-Clique Densest Subgraph Detection | 2023 | SIGMOD | 7.2572837e-05 |
| 3,993 | Efficient k-Clique Listing: An Edge-Oriented Branching Strategy | 2024 | SIGMOD | 6.9688824e-05 |
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