Embedded locality discriminant GPLVM for dimensionality reduction.
Bing HanLixia ZhangXinbo GaoXiaojing ZhaoDacheng TaoPublished in: IJCNN (2016)
Keyphrases
- dimensionality reduction
- principal component analysis
- low dimensional
- locality preserving projections
- feature extraction
- linear discriminant
- linear dimensionality reduction
- class separability
- locality preserving
- linear discriminant analysis
- discriminant projection
- discriminant analysis
- high dimensionality
- feature selection
- pattern recognition
- high dimensional
- data points
- structure preserving
- discriminant information
- embedded systems
- data representation
- pattern recognition and machine learning
- nonlinear dimensionality reduction
- manifold learning
- lower dimensional
- input space
- principal components
- random projections
- dimensionality reduction methods
- feature space
- pairwise
- spatial locality
- kernel pca
- subspace learning
- high dimensional data
- fisher discriminant
- subspace analysis
- supervised dimensionality reduction
- metric learning
- graph embedding
- intrinsic dimensionality
- multidimensional scaling
- data sets
- pattern classification
- dimension reduction
- information retrieval