Tensor low-rank sparse representation for tensor subspace learning.
Shiqiang DuYuqing ShiGuangrong ShanWeilan WangYide MaPublished in: Neurocomputing (2021)
Keyphrases
- subspace learning
- sparse representation
- low rank
- dimensionality reduction
- high dimensional data
- high order
- low rank matrix recovery
- sparse coding
- singular value decomposition
- dictionary learning
- robust face recognition
- semi supervised
- face recognition
- low dimensional
- manifold learning
- higher order
- high dimensional
- convex optimization
- principal component analysis
- data representation
- linear combination
- low rank matrix
- random projections
- missing data
- image patches
- object tracking
- unsupervised learning
- image classification
- matrix factorization
- reconstruction error
- feature extraction
- kernel matrix
- compressive sensing
- linear subspace
- pattern recognition
- dimension reduction
- natural images
- signal processing
- nearest neighbor
- matrix completion
- negative matrix factorization
- norm minimization
- image data
- feature selection
- learning algorithm
- singular values
- data points
- data sets
- collaborative filtering
- image representation
- test images