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MIM-Reasoner: Learning with Theoretical Guarantees for Multiplex Influence Maximization
Feb. 28, 2024, 5:42 a.m. | Nguyen Do, Tanmoy Chowdhury, Chen Ling, Liang Zhao, My T. Thai
cs.LG updates on arXiv.org arxiv.org
Abstract: Multiplex influence maximization (MIM) asks us to identify a set of seed users such as to maximize the expected number of influenced users in a multiplex network. MIM has been one of central research topics, especially in nowadays social networking landscape where users participate in multiple online social networks (OSNs) and their influences can propagate among several OSNs simultaneously. Although there exist a couple combinatorial algorithms to MIM, learning-based solutions have been desired due to …
abstract arxiv cs.ai cs.lg cs.si identify influence landscape math.pr multiple network networking research seed set social social networking stat.ml topics type
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