ToupleGDD: A fine-designed solution of influence maximization by deep reinforcement learning

T Chen, S Yan, J Guo, W Wu - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Aiming at selecting a small subset of nodes with maximum influence on networks, the
influence maximization (IM) problem has been extensively studied. Since it is# P-hard to …
被引用次数：29 相关文章

ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning

T Chen, S Yan, J Guo, W Wu - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
Aiming at selecting a small subset of nodes with maximum influence on networks, the
Influence Maximization (IM) problem has been extensively studied. Since it is# P-hard to …
[PDF] nsf.gov

[PDF][PDF] ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning

T Chen, S Yan, J Guo, W Wu - IEEE Transactions on Computational …, 2023 - par.nsf.gov
ONLINE social platforms, such as Twitter and LinkedIn, have shown to be one of the most
effective ways for people to communicate and share information with each other. Many …

ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement Learning

T Chen, S Yan, J Guo, W Wu - arXiv preprint arXiv:2210.07500, 2022 - arxiv.org
Aiming at selecting a small subset of nodes with maximum influence on networks, the
Influence Maximization (IM) problem has been extensively studied. Since it is# P-hard to …