In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning.
Mamshad Nayeem RizveKevin DuarteYogesh Singh RawatMubarak ShahPublished in: CoRR (2021)
Keyphrases
- semi supervised learning
- label propagation
- semi supervised
- manifold regularization
- unsupervised learning
- active learning
- labeled data
- unlabeled data
- supervised learning
- partially labeled
- discriminative models
- regularization framework
- text categorization
- machine learning
- multi view learning
- boosting framework
- pairwise
- semi supervised classification
- semi supervised learning algorithms
- multiple instance learning
- graph construction
- multi instance learning
- graph based semi supervised learning
- instance selection
- multi label classification
- class labels
- training data
- semi supervised clustering
- labeled examples
- co training
- learning models
- training set
- image segmentation