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Apr, 2024
子群移位下的新颖节点类别检测
Novel Node Category Detection Under Subpopulation Shift
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Hsing-Huan Chung, Shravan Chaudhari, Yoav Wald, Xing Han, Joydeep Ghosh
TL;DR
通过结合受限制的回溯学习框架和高效的图链接预测机制,我们引入了一种新的方法,受限制的召回率优化与选择性链接预测(RECO-SLIP),以在具有次群体转变的带属性图中检测属于新类别的节点,并在多个图数据集上进行了全面的实证评估,证明了RECO-SLIP方法在性能上的优势。
Abstract
In real-world graph data,
distribution shifts
can manifest in various ways, such as the emergence of new categories and changes in the relative proportions of existing categories. It is often important to detect nodes of
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