Low-rank quadrature-based tensor approximation of the Galerkin projected Newton/Yukawa kernels.
Cristóbal BertoglioBoris N. KhoromskijPublished in: Comput. Phys. Commun. (2012)
Keyphrases
- low rank
- frobenius norm
- linear combination
- kernel matrices
- trace norm
- high order
- tensor decomposition
- matrix decomposition
- missing data
- convex optimization
- low rank approximation
- matrix completion
- matrix factorization
- low rank matrix
- singular value decomposition
- kernel matrix
- interior point methods
- rank minimization
- high dimensional data
- partial differential equations
- semi supervised
- data matrix
- higher order
- kernel learning
- singular values
- multi task
- diffusion tensor
- data representation
- support vector
- positive definite
- approximation methods
- reconstruction error
- sparse coding
- kernel methods
- least squares
- data sets
- dimensionality reduction
- feature space