Influence Maximization in Near-Linear Time: A Martingale Approach
Summary: Near-linear-time influence maximization using martingale-based estimators. Maintains the same (1-1/e-ε)-approx guarantees as the state of the art, while delivering orders-of-magnitude speedups and broader diffusion-model support on networks up to 1.4B edges. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Youze Tang (Nanyang Technological University)
- 2. Yanchen Shi (Nanyang Technological University)
- 3. Xiaokui Xiao (Nanyang Technological University)
BibTeX Citation
@inproceedings{tang_sigmod15,
title = {{Influence Maximization in Near-Linear Time: A Martingale Approach}},
author = {Tang, Youze and Shi, Yanchen and Xiao, Xiaokui},
series = {{SIGMOD} '15},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2723372.2723734},
url = {https://dl.acm.org/doi/10.1145/2723372.2723734},
year = {2015}
}Incoming Citations (Sorted by Pagerank)
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Showing 2 of 2 cited papers.
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 |
| 296 | A Data-Based Approach to Social Influence Maximization | 2012 | VLDB | 0.00022220351 |
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