Subspace manifold learning with sample weights.
Nathan MekuzChristian BauckhageJohn K. TsotsosPublished in: Image Vis. Comput. (2009)
Keyphrases
- manifold learning
- low dimensional
- subspace learning
- dimensionality reduction
- high dimensional data
- high dimensional
- locality preserving
- locality preserving projections
- dimension reduction
- feature space
- principal component analysis
- feature extraction
- nonlinear dimensionality reduction
- linear subspace
- semi supervised
- manifold structure
- diffusion maps
- nonlinear manifold
- laplacian eigenmaps
- locally linear embedding
- input space
- lower dimensional
- subspace clustering
- sparse representation
- linear combination
- pattern recognition
- vector space
- head pose estimation
- low dimensional manifolds
- high dimensional image space
- manifold embedding
- data analysis
- preprocessing
- pairwise
- discriminant analysis
- dimensionality reduction methods
- riemannian manifolds
- feature selection
- euclidean space