Enhancing Graph Neural Networks via auxiliary training for semi-supervised node classification.
Yao WuYu SongHong HuangFanghua YeXing XieHai JinPublished in: Knowl. Based Syst. (2021)
Keyphrases
- semi supervised
- training process
- neural network
- supervised learning
- semi supervised classification
- pattern recognition
- multi layer perceptron
- directed graph
- training set
- training phase
- graph structure
- training samples
- training algorithm
- training patterns
- classification accuracy
- feature extraction
- decision trees
- support vector machine
- pattern classification
- label propagation
- undirected graph
- labeled and unlabeled data
- co training
- machine learning
- partially labeled data
- graph construction
- unlabeled samples
- classification algorithm
- unsupervised learning
- semi supervised learning
- unlabeled data
- artificial neural networks
- support vector
- image classification
- multi view
- label information
- training examples
- class labels
- incremental learning
- recurrent neural networks
- feature selection
- labelled data
- radial basis function
- feature space
- benchmark classification problems
- feature vectors
- radial basis function network
- feedforward neural networks
- support vector machine svm
- bipartite graph