Stop-and-Stare: Optimal Sampling Algorithms for Viral Marketing in Billion-scale Networks
Summary: SSA and D-SSA: fast sampling frameworks for Influence Maximization in billion-scale networks, offering up to 1200× speedups over IMM with (1−1/e−ε) guarantee. Stop-and-Stare uses exponential checkpoints to certify quality, achieving minimal sampling with strong theoretical guarantees. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Hung T. Nguyen (Virginia Commonwealth University)
- 2. My T. Thai (University of Florida)
- 3. Thang N. Dinh (Virginia Commonwealth University)
BibTeX Citation
@inproceedings{nguyen_sigmod16,
title = {{Stop-and-Stare: Optimal Sampling Algorithms for Viral Marketing in Billion-scale Networks}},
author = {Nguyen, Hung T. and Thai, My T. and Dinh, Thang N.},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2915207},
url = {https://dl.acm.org/doi/10.1145/2882903.2915207},
year = {2016}
}
Incoming Citations (Sorted by Pagerank)
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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 |
|---|---|---|---|---|
| 194 | Influence Maximization: Near-Optimal Time Complexity Meets Practical Efficiency | 2014 | SIGMOD | 0.000259047 |
| 315 | Influence Maximization in Near-Linear Time: A Martingale Approach | 2015 | SIGMOD | 0.00021436156 |
| 2,199 | Real-time Targeted Influence Maximization for Online Advertisements | 2015 | VLDB | 8.9668012e-05 |
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