Maximum k-Plex Finding: Choices of Pruning Techniques Matter!
Summary: U-MkP unifies nine MkP solvers into branching/upper-bound/reduction primitives, showing pruning choices crucially determine runtime and that optimal technique configurations vary with k. Refutes several claimed gains, uncovers an overlooked major booster for k>5, and evaluates all/densest MkP variants and parallelism. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Akhlaque Ahmad
- 2. Da Yan
- 3. Xiao Chen
- 4. Lyuheng Yuan
- 5. Qin Zhang
- 6. Saugat Adhikari
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,650 | Efficient Enumeration of Maximal k-Plexes | 2015 | SIGMOD | 0.00011013428 |
| 4,081 | Efficient Maximum k-Plex Computation over Large Sparse Graphs | 2023 | VLDB | 6.4642761e-05 |
| 5,149 | Scalable Mining of Maximal Quasi-Cliques: An Algorithm-System Codesign Approach | 2021 | VLDB | 5.6627295e-05 |
| 5,696 | Maximum k-Plex Computation: Theory and Practice | 2024 | SIGMOD | 5.3673968e-05 |
| 9,561 | T-FSM: A Task-Based System for Massively Parallel Frequent Subgraph Pattern Mining from a Big Graph | 2023 | SIGMOD | 4.3254416e-05 |
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