Semi-supervised support vector regression based on self-training with label uncertainty: An application to virtual metrology in semiconductor manufacturing.
Pilsung KangDongil KimSungzoon ChoPublished in: Expert Syst. Appl. (2016)
Keyphrases
- semiconductor manufacturing
- semi supervised
- support vector
- process control
- semi supervised learning
- co training
- label propagation
- label information
- gaussian process
- discrete event simulation
- labeled data
- svm classifier
- unlabeled data
- semi supervised classification
- kernel logistic regression
- partially labeled
- active learning
- supervised learning
- multi label classification
- pairwise
- virtual reality
- pairwise constraints
- unsupervised learning
- virtual environment
- support vector machine
- feature selection
- augmented reality
- production system
- multi view
- class labels
- cross validation
- hyperplane
- uncertain data
- generalization ability
- control system
- virtual world
- training examples
- semi supervised clustering
- kernel function
- classification accuracy
- artificial intelligence
- labeled and unlabeled data
- multi class
- labeled examples
- binary classification
- logistic regression
- maximum margin
- data points
- single view
- metric learning
- multi label
- training set
- data sets