Semi-Supervised Discriminative Classification Robust to Sample-Outliers and Feature-Noises.
Ehsan AdeliKim-Han ThungLe AnGuorong WuFeng ShiTao WangDinggang ShenPublished in: IEEE Trans. Pattern Anal. Mach. Intell. (2019)
Keyphrases
- sample size
- semi supervised
- model selection
- highly discriminative
- discriminative features
- supervised learning
- unsupervised learning
- feature vectors
- feature extraction
- semi supervised classification
- labeled and unlabeled data
- semi supervised learning
- pattern recognition
- label information
- classification accuracy
- co training
- feature set
- feature representation
- image classification
- unlabeled samples
- classification method
- decision trees
- support vector machine svm
- outlier detection
- feature selection
- classification algorithm
- labeled data
- image features
- machine learning
- active learning
- object recognition
- training data
- feature space
- salt pepper
- low rank representation
- object category recognition
- robust statistical
- robust classification
- discriminating power
- discriminative training
- single feature
- similarity measure
- class labels
- pairwise
- support vector machine
- feature descriptors
- low rank
- feature subset
- noisy data
- text classification
- training samples