Contingency-aware influence maximization: A reinforcement learning approach

H Chen, W Qiu, HC Ou, B An… - Uncertainty in Artificial …, 2021 - proceedings.mlr.press
The influence maximization (IM) problem aims at finding a subset of seed nodes in a social
network that maximize the spread of influence. In this study, we focus on a sub-class of IM …
被引用次数：21 相关文章

Contingency-Aware Influence Maximization: A Reinforcement Learning Approach

H Chen, W Qiu, HC Ou, B An, M Tambe - arXiv preprint arXiv:2106.07039, 2021 - arxiv.org
The influence maximization (IM) problem aims at finding a subset of seed nodes in a social
network that maximize the spread of influence. In this study, we focus on a sub-class of IM …
[PDF] openreview.net

[PDF][PDF] Contingency-Aware Influence Maximization: A Reinforcement Learning Approach

H Chen, W Qiu, HC Ou, B An, M Tambe - openreview.net
The influence maximization (IM) problem aims at finding a subset of seed nodes in a social
network that maximize the spread of influence. In this study, we focus on a sub-class of IM …

Contingency-Aware Influence Maximization: A Reinforcement Learning Approach

H Chen, W Qiu, HC Ou, B An, M Tambe - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
The influence maximization (IM) problem aims at finding a subset of seed nodes in a social
network that maximize the spread of influence. In this study, we focus on a sub-class of IM …
[PDF] auai.org

[PDF][PDF] Contingency-Aware Influence Maximization: A Reinforcement Learning Approach

H Chen, W Qiu, HC Ou, B An, M Tambe - auai.org
The influence maximization (IM) problem aims at finding a subset of seed nodes in a social
network that maximize the spread of influence. In this study, we focus on a sub-class of IM …
[PDF] auai.org

[PDF][PDF] Contingency-Aware Influence Maximization: A Reinforcement Learning Approach

H Chen, W Qiu, HC Ou, B An, M Tambe - auai.org
The influence maximization (IM) problem aims at finding a subset of seed nodes in a social
network that maximize the spread of influence. In this study, we focus on a sub-class of IM …
[PDF] umich.edu

[PDF][PDF] Contingency-Aware Influence Maximization: A Reinforcement Learning Approach

H Chen, W Qiu, HC Ou, B An, M Tambe - network-games-muri.engin.umich …
The influence maximization (IM) problem aims at finding a subset of seed nodes in a social
network that maximize the spread of influence. In this study, we focus on a sub-class of IM …
[PDF] harvard.edu

[PDF][PDF] Contingency-Aware Influence Maximization: A Reinforcement Learning Approach

H Chen, W Qiu, HC Ou, B An, M Tambe - teamcore.seas.harvard.edu
The influence maximization (IM) problem aims at finding a subset of seed nodes in a social
network that maximize the spread of influence. In this study, we focus on a sub-class of IM …
[PDF] ntu.edu.sg

[PDF][PDF] Contingency-Aware Influence Maximization: A Reinforcement Learning Approach

H Chen, W Qiu, HC Ou, B An, M Tambe - personal.ntu.edu.sg
The influence maximization (IM) problem aims at finding a subset of seed nodes in a social
network that maximize the spread of influence. In this study, we focus on a sub-class of IM …
[PDF] harvard.edu

[PDF][PDF] Contingency-Aware Influence Maximization: A Reinforcement Learning Approach

H Chen, W Qiu, HC Ou, B An, M Tambe - projects.iq.harvard.edu
The influence maximization (IM) problem aims at finding a subset of seed nodes in a social
network that maximize the spread of influence. In this study, we focus on a sub-class of IM …