Multi-teacher Self-training for Semi-supervised Node Classification with Noisy Labels.
Yujing LiuZongqian WuZhengyu LuGuoqiu WenJunbo MaGuangquan LuXiaofeng ZhuPublished in: ACM Multimedia (2023)
Keyphrases
- learning algorithm
- semi supervised
- co training
- supervised learning
- unlabeled data
- semi supervised learning
- active learning
- labeled data
- semi supervised classification
- unlabeled samples
- label information
- class labels
- partially labeled data
- classification algorithm
- machine learning
- training samples
- fully supervised
- training set
- unsupervised learning
- labeled and unlabeled data
- pairwise
- learning process
- cost sensitive
- labeled examples
- label propagation
- partially labeled
- multi label classification
- semi supervised learning algorithms
- multi view
- single view
- incremental learning
- pairwise constraints
- labeling process
- classification accuracy
- pattern recognition
- supervised classification
- support vector machine svm
- text classification
- feature selection
- model selection
- image classification
- support vector machine
- multi label learning
- data sets
- confidence scores
- feature extraction
- support vector
- binary classifiers
- benchmark datasets
- feature vectors
- feature set