Adversarial graph node classification based on unsupervised learning and optimized loss functions.
Hongli DingZhao MaChunyu XuXiaofeng WangXiaohu LuoJing ZhuPublished in: J. Ambient Intell. Humaniz. Comput. (2024)
Keyphrases
- loss function
- unsupervised learning
- support vector
- hinge loss
- supervised learning
- classification accuracy
- logistic regression
- pairwise
- text classification
- machine learning
- pattern classification
- risk minimization
- pattern recognition
- partially labeled data
- graph structure
- squared error
- support vector machine svm
- training set
- learning to rank
- loss minimization
- benchmark datasets
- binary classification
- reproducing kernel hilbert space
- feature space
- feature extraction
- feature selection
- training samples
- semi supervised learning
- maximum likelihood
- cost sensitive
- support vector machine
- decision boundary
- bregman divergences