A Riemannian Optimization Approach for Computing Low-Rank Solutions of Lyapunov Equations.
Bart VandereyckenStefan VandewallePublished in: SIAM J. Matrix Anal. Appl. (2010)
Keyphrases
- low rank
- nuclear norm
- linear combination
- matrix completion
- convex optimization
- matrix factorization
- missing data
- low rank matrix
- rank minimization
- singular value decomposition
- semi supervised
- matrix decomposition
- high dimensional data
- high order
- kernel matrix
- trace norm
- minimization problems
- low rank matrices
- robust principal component analysis
- singular values
- euclidean space
- convex relaxation
- quadratic programming
- neural network
- input data
- small number
- image processing
- data mining