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Efficient Algorithms for Adaptive Influence Maximization

Summary: Introduces AdaptGreedy, the first practical batch-adaptive influence-maximization algorithms with provable guarantees as seeds are selected after observing prior cascades. EPIC reduces expected approximation error, improving adaptive performance over existing non-adaptive IM subroutines in theory and experiments. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
11785
Venue
VLDB
Year
2018
Pagerank
6.5010703e-05
Overall Rank
4,804 | 67.05%
DOI
10.14778/3213880.3213883

Incoming Non-self Citations Over Time

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BibTeX Citation

@article{han_vldb18,
        title = {{Efficient Algorithms for Adaptive Influence Maximization}},
        author = {Han, Kai and Huang, Keke and Xiao, Xiaokui and Tang, Jing and Sun, Aixin and Tang, Xueyan},
        journal = {PVLDB},
        series = {{VLDB} '18},
        volume = {11},
        number = {9},
        pages = {1029--1040},
        doi = {10.14778/3213880.3213883},
        url = {https://doi.org/10.14778/3213880.3213883},
        year = {2018}
}

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