Symmetric low-rank preserving projections for subspace learning.
Jie ChenHua MaoHaixian ZhangZhang YiPublished in: Neurocomputing (2018)
Keyphrases
- low rank
- subspace learning
- high dimensional data
- semi supervised
- dimensionality reduction
- low rank approximation
- singular value decomposition
- linear combination
- manifold learning
- missing data
- sparse coding
- convex optimization
- matrix factorization
- low dimensional
- kernel matrix
- high dimensional
- linear subspace
- sparse representation
- principal component analysis
- background modeling
- face recognition
- nearest neighbor
- active learning
- robust face recognition
- data representation
- unsupervised learning
- data analysis
- data points
- dimension reduction
- high order
- training set
- subspace clustering
- support vector
- computer vision
- neural network
- machine learning