Nonconvex Splitting for Regularized Low-Rank + Sparse Decomposition.
Rick ChartrandPublished in: IEEE Trans. Signal Process. (2012)
Keyphrases
- low rank
- low rank matrices
- convex optimization
- ell norm
- robust principal component analysis
- sparsity constraints
- tensor decomposition
- sparse linear
- nuclear norm
- trace norm
- low rank matrix
- norm minimization
- matrix completion
- singular value decomposition
- low rank subspace
- rank minimization
- linear combination
- low rank matrix recovery
- matrix factorization
- missing data
- kernel matrix
- sparse regression
- regularized regression
- semi supervised
- matrix decomposition
- singular values
- high dimensional data
- low rank and sparse
- kernel matrices
- high order
- least squares
- low rank approximation
- minimization problems
- low rank representation
- group lasso
- objective function
- interior point methods
- data sets
- data matrix