Theoretical framework in graph embedding-based discriminant dimensionality reduction.
Guodong ZhaoZhiyong ZhouJunming ZhangPublished in: Signal Process. (2021)
Keyphrases
- theoretical framework
- graph embedding
- dimensionality reduction
- discriminant embedding
- discriminant analysis
- low dimensional
- discriminant information
- principal component analysis
- class separability
- locality preserving projections
- feature extraction
- high dimensional
- subspace learning
- semi supervised dimensionality reduction
- data representation
- linear discriminant analysis
- embedding space
- dimensionality reduction methods
- feature selection
- data points
- manifold learning
- high dimensional data
- pattern recognition
- high dimensionality
- euclidean distance
- label information
- semi supervised
- nonlinear dimensionality reduction
- dimension reduction
- feature space
- unsupervised learning
- natural images
- fundamental principles
- sparse representation
- geometric properties
- data sets