Subspace learning in the presence of sparse structured outliers and noise.
Shervin MinaeeYao WangPublished in: ISCAS (2017)
Keyphrases
- subspace learning
- sparse representation
- sparse coding
- missing data
- dimensionality reduction
- low rank approximation
- data representation
- low dimensional
- manifold learning
- principal component analysis
- data points
- high dimensional
- linear subspace
- learning algorithm
- maximum margin criterion
- natural images
- linear combination
- high dimensional data
- semi supervised
- subspace learning algorithm
- image classification
- unsupervised learning
- face recognition
- image representation
- image patches
- linear discriminant analysis
- test images
- input data
- data analysis
- pattern recognition
- feature extraction
- computer vision