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Found 4 papers, 1 papers with code
CLNode: Curriculum Learning for Node Classification
Experimental results on real-world networks demonstrate that CLNode is a general framework that can be combined with various GNNs to improve their accuracy and robustness.
Understanding Partial Multi-Label Learning via Mutual Information
To deal with ambiguities in partial multilabel learning (PML), state-of-the-art methods perform disambiguation by identifying ground-truth labels directly.
Fast Multi-label Learning
The goal of this paper is to provide a simple method, yet with provable guarantees, which can achieve competitive performance without a complex training process.
Online Metric Learning for Multi-Label Classification
Specifically, in order to learn the new $k$NN-based metric, we first project instances in the training dataset into the label space, which make it possible for the comparisons of instances and labels in the same dimension.
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