Every node counts: Self-ensembling graph convolutional networks for semi-supervised learning.
Yawei LuoRongrong JiTao GuanJunqing YuPing LiuYi YangPublished in: Pattern Recognit. (2020)
Keyphrases
- semi supervised learning
- graph based semi supervised learning
- graph construction
- label propagation
- semi supervised classification
- edge weights
- semi supervised
- graph structure
- unlabeled data
- labeled data
- directed graph
- degree distribution
- machine learning
- unsupervised learning
- graph laplacian
- supervised learning
- active learning
- training data
- semi supervised learning methods
- manifold regularization
- undirected graph
- bipartite graph
- co training
- spanning tree
- community detection
- social networks
- sparse coding
- network structure
- transfer learning
- random walk
- text classification
- semi supervised learning algorithms
- learning algorithm
- weighted graph
- protein interaction networks
- pattern recognition