Low-Rank Approximate Inverse for Preconditioning Tensor-Structured Linear Systems.
Loïc GiraldiAnthony NouyGrégory LegrainPublished in: SIAM J. Sci. Comput. (2014)
Keyphrases
- linear systems
- low rank
- trace norm
- high order
- tensor decomposition
- dynamical systems
- sufficient conditions
- linear combination
- singular value decomposition
- missing data
- linear equations
- matrix factorization
- convex optimization
- rank minimization
- low rank matrix
- matrix completion
- kernel matrix
- high dimensional data
- higher order
- semi supervised
- sparse linear systems
- dimensionality reduction
- singular values
- pairwise
- multi task
- tensor factorization
- small number
- reinforcement learning
- face recognition