Efficient Maximum s-Bundle Search via Local Vertex Connectivity
Summary: SymBD, a branch-and-bound solver for the maximum s-bundle problem (cohesive subgraph resilient to vertex deletions) using local-vertex-connectivity based orderings. Achieves O*(λ_s^n) with λ_s<2; includes heuristic initial solution, divide-and-conquer, and parallelization, with up to five orders of magnitude speedup on 664 graphs. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yang Liu (Harbin Engineering University)
- 2. Hejiao Huang (Harbin Engineering University)
- 3. Kaiqiang Yu (Nanyang Technological University)
- 4. Shengxin Liu (Harbin Engineering University)
- 5. Cheng Long (Nanyang Technological University)
BibTeX Citation
@inproceedings{liu_sigmod25,
title = {{Efficient Maximum s-Bundle Search via Local Vertex Connectivity}},
author = {Liu, Yang and Huang, Hejiao and Yu, Kaiqiang and Liu, Shengxin and Long, Cheng},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3709687},
url = {https://dl.acm.org/doi/10.1145/3709687},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,365 | Efficient Defective Clique Enumeration and Search with Worst-Case Optimal Search Space | 2026 | SIGMOD | 5.093636e-05 |
| 10,367 | Efficient Size-Bounded Community Search, Revisited: Frameworks for Practical Improvements | 2026 | SIGMOD | 5.093636e-05 |
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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