A Semi-supervised Learning Algorithm Based on Low Rank and Weighted Sparse Graph for Face Recognition.
Tao ZhangZhenmin TangBin QianPublished in: CCBR (2016)
Keyphrases
- low rank
- face recognition
- low rank matrix
- rank minimization
- low rank and sparse
- low rank subspace
- low rank matrices
- nuclear norm
- convex optimization
- robust principal component analysis
- low rank representation
- matrix factorization
- weighted graph
- linear combination
- missing data
- regularized regression
- kernel matrices
- singular value decomposition
- sparse representation
- low rank approximation
- kernel matrix
- semi supervised
- matrix completion
- matrix decomposition
- signal recovery
- high order
- tensor decomposition
- high dimensional data
- computer vision
- minimization problems
- face recognition systems
- affinity matrix
- graph matching
- sparse coding
- face images
- collaborative filtering
- approximation methods
- feature extraction
- principal component analysis
- norm minimization
- sparse matrix
- adjacency matrix
- compressive sensing
- high dimensional
- subspace learning
- small number
- total variation