On optimality of approximate low rank solutions of large-scale matrix equations.
Peter BennerTobias BreitenPublished in: Syst. Control. Lett. (2014)
Keyphrases
- low rank
- singular value decomposition
- linear combination
- low rank matrix
- matrix decomposition
- matrix completion
- missing data
- matrix factorization
- convex optimization
- rank minimization
- trace norm
- kernel matrix
- singular values
- low rank matrix approximation
- frobenius norm
- optimal solution
- semi supervised
- robust principal component analysis
- kernel matrices
- low rank approximation
- high order
- factorization methods
- high dimensional data
- low rank matrices
- data matrix
- affinity matrix
- nuclear norm
- negative matrix factorization
- denoising
- data sets
- low rank and sparse
- machine learning