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Reliable Data Distillation on Graph Convolutional Network

Summary: Reliable Data Distillation defines node and edge reliability to leverage unlabeled data in semi-supervised GCNs. Proposes a data-reliability–driven ensemble and a Self-Boosting SSL framework to curb teacher bias and cost, yielding state-of-the-art semi-supervised node classification. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
5921
Venue
SIGMOD
Year
2020
Pagerank
5.0074274e-05
Overall Rank
6,566 | 54.33%
DOI
10.1145/3318464.3389706

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