Finding a low-rank basis in a matrix subspace
For a given matrix subspace, how can we find a basis that consists of low-rank matrices? This is a generalization of the sparse vector problem. It turns out that when the subspace is spanned by rank-1 matrices, the matrices can be obtained by the tensor CP decomposition. For the higher rank case, th...
Autori principali: | Nakatsukasa, Y, Soma, T, Uschmajew, A |
---|---|
Natura: | Journal article |
Lingua: | English |
Pubblicazione: |
Springer Verlag
2016
|
Documenti analoghi
Documenti analoghi
-
On orthogonal tensors and best rank-one approximation ratio
di: Li, Z, et al.
Pubblicazione: (2018) -
Low-rank matrix approximations over canonical subspaces
di: Achiya Dax
Pubblicazione: (2020-09-01) -
Low-rank matrix approximations over canonical subspaces
di: Achiya Dax
Pubblicazione: (2020-09-01) -
Low-rank matrix approximations over canonical subspaces
di: Achiya Dax
Pubblicazione: (2020-09-01) -
Low-rank matrix approximations over canonical subspaces
di: Achiya Dax
Pubblicazione: (2020-09-01)