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Semi-supervised Adversarial Active Learning on Attributed Graphs
[article]
2019
arXiv
pre-print
Active learning (AL) on attributed graphs has received increasing attention with the prevalence of graph-structured data. Although AL has been widely studied for alleviating label sparsity issues with the conventional independent and identically distributed (i.i.d.) data, how to make it effective over attributed graphs remains an open research question. Existing AL algorithms on graphs attempt to reuse the classic AL query strategies designed for i.i.d. data. However, they suffer from two major
arXiv:1908.08169v1
fatcat:i2olskc7vvcodeqzsgyfvpctue