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Mar, 2022
通过图形拓扑导出的最优运输优化微调图神经网络
Fine-Tuning Graph Neural Networks via Graph Topology induced Optimal Transport
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Jiying Zhang, Xi Xiao, Long-Kai Huang, Yu Rong, Yatao Bian
TL;DR
本研究提出了一种基于最优传输的微调框架,称为图拓扑诱导的最优传输微调(GTOT-Tuning),用于增强在图学习上预训练模型微调的表示保存性,并证明它在各种图神经网络模型上比现有技术表现更好。
Abstract
Recently, the
pretrain-finetuning paradigm
has attracted tons of attention in
graph learning community
due to its power of alleviating the lack of labels problem in many real-world applications. Current studies u
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