Joint latent low-rank and non-negative induced sparse representation for face recognition.
Mingna WuShu WangZhigang LiLong ZhangLing WangZhenwen RenPublished in: Appl. Intell. (2021)
Keyphrases
- sparse representation
- low rank
- face recognition
- high dimensional data
- low rank matrix recovery
- group sparsity
- dictionary learning
- sparse coding
- linear combination
- missing data
- robust face recognition
- matrix factorization
- low rank matrix
- convex optimization
- singular value decomposition
- dimensionality reduction
- sparsity constraints
- image patches
- matrix completion
- compressed sensing
- semi supervised
- random projections
- reconstruction error
- kernel matrix
- face images
- nearest neighbor
- subspace learning
- high dimensional
- compressive sensing
- image classification
- high order
- latent variables
- feature extraction
- low dimensional
- signal processing
- singular values
- data sets
- collaborative filtering
- negative matrix factorization
- data analysis
- image representation
- data points
- training data
- latent space
- interior point methods
- natural images
- norm minimization
- active learning
- recommender systems