AdaGCN combines graph convolutional networks with adversarial domain adaptation to classify nodes in an unlabeled target network using labels from a related source network.
A theory of learning from different domains,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Graph Transfer Learning via Adversarial Domain Adaptation with Graph Convolution
AdaGCN combines graph convolutional networks with adversarial domain adaptation to classify nodes in an unlabeled target network using labels from a related source network.