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Efficient Maximum k-Defective Clique Computation with Improved Time Complexity

Summary: Introduces kDC, a framework for exact maximum k-defective clique with sub-2^n time, via non-fully-adjacent-first branching, excess-removal, and high-degree reductions. Separates worst-case techniques from practical optimizations; adds a tighter upper bound, two reductions, and fast initial solution; benchmarks on 290 graphs show kDC vastly outperforms KDBB. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h7a605739ad4f0709
Venue
SIGMOD
Year
2023
Pagerank
6.9663663e-05
Overall Rank
3,860 | 74.05%
DOI
10.1145/3617313

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{chang_sigmod23,
        title = {{Efficient Maximum k-Defective Clique Computation with Improved Time Complexity}},
        author = {Chang, Lijun},
        series = {{SIGMOD} '23},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3617313},
        url = {https://dl.acm.org/doi/10.1145/3617313},
        year = {2023}
}

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
100 Truss Decomposition in Massive Networks 2012 VLDB 0.00033977856
988 Dense Subgraph Maintenance under Streaming Edge Weight Updates for Real-time Story Identification 2012 VLDB 0.00012660447
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