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Graph-based approaches have been most successful in semisupervised learning. In this paper, we focus on label propagation in graph-based semisupervised learning. One essential point of label ...
Various graph-based algorithms for semi-supervised learning have been proposed in the recent literature. They rely on the idea of building a graph whose nodes are data points (labeled and unlabeled) ...
Abstract: Graph Neural Networks (GNNs) have been widely applied in the semi-supervised node classification task, where a key point lies in how to sufficiently leverage the limited but valuable label ...
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