Low-rank sparse feature selection for image classification.
Weigang WangJuchao MaChendong XuYunwei ZhangYa DingShujuan YuYun ZhangYuanjian LiuPublished in: Expert Syst. Appl. (2022)
Keyphrases
- low rank
- image classification
- feature selection
- low rank matrix
- rank minimization
- low rank subspace
- low rank matrices
- nuclear norm
- feature extraction
- low rank representation
- linear combination
- robust principal component analysis
- sparse coding
- convex optimization
- sparse representation
- matrix factorization
- kernel matrices
- singular value decomposition
- regularized regression
- matrix completion
- missing data
- image representation
- high dimensional data
- matrix decomposition
- low rank approximation
- dimensionality reduction
- high order
- kernel matrix
- semi supervised
- image features
- tensor decomposition
- visual words
- sparse matrix
- support vector machine
- data matrix
- trace norm
- multi label
- text classification
- support vector
- singular values
- minimization problems
- affinity matrix
- unsupervised feature selection
- dictionary learning
- text categorization
- elastic net
- nearest neighbor
- feature vectors
- high dimensional
- feature space
- low rank and sparse
- feature subset
- higher order