Dimensionality reduction via kernel sparse representation.
Zhisong PanZhantao DengYibing WangYanyan ZhangPublished in: Frontiers Comput. Sci. (2014)
Keyphrases
- sparse representation
- dimensionality reduction
- feature space
- high dimensional data
- kernel pca
- input space
- regularized least squares
- kernel learning
- dictionary learning
- high dimensional
- random projections
- principal component analysis
- data representation
- low dimensional
- subspace learning
- sparse coding
- graph embedding
- manifold learning
- unsupervised learning
- pattern recognition
- high dimensionality
- feature selection
- image patches
- kernel function
- linear discriminant analysis
- joint optimization
- sparse approximations
- principal components
- compressive sensing
- lower dimensional
- compressed sensing
- feature extraction
- support vector
- kernel methods
- data sets
- negative matrix factorization
- data points
- singular value decomposition
- positive definite
- image processing
- dimension reduction
- nearest neighbor
- denoising
- image representation
- image reconstruction