"Low-rank + dual" model based dimensionality reduction.
Si-Qi WangXiang-Chu FengWeiwei WangPublished in: Neurocomputing (2016)
Keyphrases
- low rank
- dimensionality reduction
- high dimensional data
- singular value decomposition
- low rank matrix
- low dimensional
- matrix completion
- missing data
- convex optimization
- kernel matrix
- high dimensional
- linear combination
- rank minimization
- high dimensionality
- matrix factorization
- manifold structure
- principal component analysis
- pattern recognition
- matrix decomposition
- singular values
- data representation
- primal dual
- random projections
- high order
- semi supervised
- feature selection
- kernel learning
- feature space
- manifold learning
- data sets
- principal components
- kernel pca
- trace norm
- non rigid structure from motion
- robust principal component analysis
- original data
- missing values
- feature extraction
- data analysis
- nearest neighbor
- data points
- low rank matrices
- machine learning
- minimization problems
- metric learning
- data matrix
- euclidean distance
- subspace learning
- higher order
- super resolution
- image processing
- computer vision
- data mining