Name
Abstract | ||
|---|---|---|
This paper proposes a constrained canonical polyadic (CP) tensor decomposition method with low-rank factor matrices. In this way, we allow the CP decomposition with high rank while keeping the number of the model parameters small. First, we propose an algorithm to decompose the tensors into factor matrices of given ranks. Second, we propose an algorithm which can determine the ranks of the factor matrices automatically, such that the fitting error is bounded by a user-selected constant. The algorithms are verified on the decomposition of a tensor of the MNIST hand-written image dataset. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICASSP39728.2021.9414606 | 2021 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP 2021) |
Keywords | DocType | Citations |
CANDECOMP, PARAFAC, low-rank constraint, rank minimization, tensor decomposition | Conference | 0 |
PageRank | References | Authors |
0.34 | 12 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anh Huy Phan | 1 | 828 | 51.60 |
| Petr Tichavský | 2 | 341 | 41.01 |
| Konstantin Sobolev | 3 | 0 | 0.34 |
| Konstantin Sozykin | 4 | 0 | 0.34 |
| Dmitry Ermilov | 5 | 0 | 0.34 |
| Andrzej Cichocki | 6 | 5228 | 508.42 |