Efficient Algorithms for Densest Subgraph Discovery
Summary: Reduces densest-subgraph discovery to strategically identifying k-cores, enabling exact and approximation algorithms with guarantees. Generalizes across edge-, clique-, and pattern-based densities, achieving up to 10,000× speedups over prior methods. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Yixiang Fang (Guangdong University of Technology; University of New South Wales; Zhejiang Lab)
- 2. Kaiqiang Yu (University of Hong Kong)
- 3. Reynold Cheng (University of Hong Kong)
- 4. Laks V.S. Lakshmanan (University of British Columbia)
- 5. Xuemin Lin (University of New South Wales; Zhejiang Lab)
BibTeX Citation
@article{fang_vldb19,
title = {{Efficient Algorithms for Densest Subgraph Discovery}},
author = {Fang, Yixiang and Yu, Kaiqiang and Cheng, Reynold and Lakshmanan, Laks V.S. and Lin, Xuemin},
journal = {PVLDB},
series = {{VLDB} '19},
volume = {12},
number = {11},
pages = {1719--1732},
doi = {10.14778/3342263.3342645},
url = {https://doi.org/10.14778/3342263.3342645},
year = {2019}
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