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arXiv Machine Learning By Yiqiao Liao, Parinaz Naghizadeh

Rethinking Learning-Based Influence Maximization: Simple Neural Surrogates and Native Discrete Search

Read the original on arXiv Machine Learning →

arXiv:2608. 08406v1 Announce Type: new Abstract: Existing learning-based influence maximization frameworks rely heavily on complex neural architectures and continuous optimization over seed representations.

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