Abstract: Label distribution learning (LDL), leveraging the label significance (LS), is more appropriate for solving label ambiguity problems than multilabel learning (MLL). However, directly ...
Abstract: Graph Neural Networks (GNNs) have become a powerful tool for processing graph-structured data. However, real-world data often faces the problem of label noise and sparsity, which will ...
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