Semi-supervised double sparse graphs based discriminant analysis for dimensionality reduction.
Puhua ChenLicheng JiaoFang LiuJiaqi ZhaoZhiqiang ZhaoShuai LiuPublished in: Pattern Recognit. (2017)
Keyphrases
- graph embedding
- discriminant analysis
- semi supervised
- dimensionality reduction
- linear discriminant analysis
- high dimensional
- subspace learning
- fisher discriminant analysis
- principal component analysis
- dimensionality reduction methods
- feature extraction
- sparse representation
- semi supervised learning
- low dimensional
- kernel discriminant analysis
- random projections
- fisher criterion
- discriminant subspace
- face recognition
- high dimensional data
- label information
- labeled data
- linear discriminant
- active learning
- manifold learning
- unsupervised learning
- sparse coding
- pairwise
- low rank
- supervised learning
- feature space
- canonical correlation analysis
- dimension reduction
- document clustering
- pattern recognition
- data representation
- metric learning
- multi class
- discriminant projection
- neural network
- class separability
- partial least squares
- input space
- high dimensionality
- cluster analysis
- unlabeled data