Efficient Algorithms for Influence Maximization in General Models and Observed Cascades

Spaeh, Fabian; Haris, Themistoklis; Ene, Alina; Nguyen, Huy L.

doi:10.24963/ijcai.2026/40

Efficient Algorithms for Influence Maximization in General Models and Observed Cascades

Fabian Spaeh, Themistoklis Haris, Alina Ene, Huy L. Nguyen

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Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. Main Track. Pages 348-356.

https://doi.org/10.24963/ijcai.2026/40

Keywords

Agent-based and Multi-agent Systems: Resource allocation
Search: Combinatorial search and optimisation
Data Mining: Mining graphs

Abstract

We study influence maximization in general stochastic models, the observed cascades model, and the independent cascade (IC) model. For general stochastic models with only black-box sample access, we introduce a low-adaptivity optimization framework that improves sample complexity and running time over the prior work and is instrumental to all our results. We further introduce an adaptive algorithm guided by empirical variance, avoiding pessimistic worst-case bounds. Combining our optimization framework with sketching, we obtain the first algorithm with provable guarantees and nearly-linear running time for influence maximization on observed cascades, optimal up to logarithmic factors. For IC, we prove a novel tail bound replacing a factor n with ? (the number of diffusion steps) in sample complexity, improving over prior work when ? is small, as is common due to small-world phenomena. Experiments confirm substantial speedups while maintaining solution quality.

Fabian Spaeh, Themistoklis Haris, Alina Ene, and Huy L. Nguyen. 2026. Efficient Algorithms for Influence Maximization in General Models and Observed Cascades. In Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26. IJCAI, 348–356. https://doi.org/10.24963/ijcai.2026/40

@inproceedings{ijcai2026p40,
  title     = {Efficient Algorithms for Influence Maximization in General Models and Observed Cascades},
  author    = {Spaeh, Fabian and Haris, Themistoklis and Ene, Alina and Nguyen, Huy L.},
  booktitle = {Proceedings of the Thirty-Fifth International Joint Conference on
               Artificial Intelligence, {IJCAI-26}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Diego Calvanese},
  pages     = {348--356},
  year      = {2026},
  month     = {8},
  note      = {Main Track},
  doi       = {10.24963/ijcai.2026/40},
  url       = {https://doi.org/10.24963/ijcai.2026/40},
}

TY  - CPAPER
TI  - Efficient Algorithms for Influence Maximization in General Models and Observed Cascades
AU  - Spaeh, Fabian
AU  - Haris, Themistoklis
AU  - Ene, Alina
AU  - Nguyen, Huy L.
T2  - Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2026
SP  - 348
EP  - 356
DO  - 10.24963/ijcai.2026/40
UR  - https://doi.org/10.24963/ijcai.2026/40
ER  -