Tensor robust principal component analysis with total generalized variation for high-dimensional data recovery.
Zhi XuJing-Hua YangChuanlong WangFusheng WangXihong YanPublished in: Appl. Math. Comput. (2024)
Keyphrases
- high dimensional data
- robust principal component analysis
- low rank
- dimensionality reduction
- high dimensional
- low dimensional
- nearest neighbor
- data sets
- subspace clustering
- high dimensionality
- data analysis
- original data
- similarity search
- high order
- sparse representation
- rank minimization
- higher order
- manifold learning
- clustering high dimensional data
- matrix completion
- principal component analysis
- data points
- kernel matrix
- linear discriminant analysis
- dimension reduction
- low rank and sparse
- variable selection
- locally linear embedding
- neural network
- singular value decomposition
- missing values
- input data
- least squares
- feature space