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The influence maximization (IM) problem aims at finding a subset of seed nodes in a social network that maximize the spread of influence.
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Maximizing social influence in nearly optimal time
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Diederik P Kingma and Jimmy Ba · 2015
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A learning-based framework to handle multi-round multi-party influence maximization on social networks
Su-Chen Lin, Shou-De Lin, and Ming-Syan Chen · 2015
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Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
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Influence maximization in near-linear time: A martingale approach
Youze Tang, Yanchen Shi, and Xiaokui Xiao · 2015
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Thomas N Kipf and Max Welling · 2016
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Using social networks to aid homeless shelters: Dynamic influence maximization under uncertainty
Amulya Yadav, Hau Chan, Albert Xin Jiang, Haifeng Xu, Eric Rice, and Milind Tambe · 2016
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Chaitanya K Joshi, Thomas Laurent, and Xavier Bresson · 2019
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Disco: Influence maximization meets network embedding and deep learning
Hui Li, Mengting Xu, Sourav S Bhowmick, Changsheng Sun, Zhongyuan Jiang, and Jiangtao Cui · 2019
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Efficient approximation algorithms for adaptive influence maximization
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Influence maximization in unknown social networks: Learning policies for effective graph sampling
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Monstor: An inductive approach for estimating and maximizing influence over unseen social networks
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Deep reinforcement learning-based approach to tackle topic-aware influence maximization
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