A Nonconvex Low Rank and Sparse Constrained Multiview Subspace Clustering via $l_{\frac{1}{2}}$-Induced Tensor Nuclear Norm.
Jobin FrancisBaburaj MadathilSudhish N. GeorgeSony GeorgePublished in: IEEE Trans. Signal Inf. Process. over Networks (2023)
Keyphrases
- low rank and sparse
- subspace clustering
- low rank
- high dimensional data
- nuclear norm
- low rank matrix
- dimensionality reduction
- high order
- matrix completion
- convex optimization
- high dimensional
- high dimensionality
- rank minimization
- nearest neighbor
- low dimensional
- singular value decomposition
- missing data
- data points
- matrix factorization
- clustering method
- higher order
- data analysis
- data sets
- linear combination
- data matrix
- sparse representation
- original data
- missing values
- clustering algorithm
- semi supervised
- singular values
- principal component analysis
- feature selection
- computer vision
- input data
- random projections
- training data
- feature extraction