SEAL trains a graph embedding network and a semisupervised discriminator adversarially so that the discriminator's divergence score selects which unlabeled nodes to label, improving node classification accuracy over prior active learning baselines.
ANRMAB improves AGE by dynamically adjusting the weights of different strategies based on the MAB reward
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SEAL: Semi-supervised Adversarial Active Learning on Attributed Graphs
SEAL trains a graph embedding network and a semisupervised discriminator adversarially so that the discriminator's divergence score selects which unlabeled nodes to label, improving node classification accuracy over prior active learning baselines.