| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0574036 |
| utime |
20240402214222.4 |
| mtime |
20230801235959.9 |
| title
(primary) (eng) |
Tensor Chain Decomposition and Function Interpolation |
| specification |
| page_count |
5 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0574035 |
| ISBN |
978-1-6654-5244-1 |
| title
|
Proceedings of the 22nd IEEE Statistical Signal Processing Workshop |
| page_num |
557-561 |
| publisher |
| place |
Piscataway |
| name |
IEEE |
| year |
2023 |
|
|
| keyword |
multilinear models |
| keyword |
tensor train |
| keyword |
Rosenbrock function |
| author
(primary) |
| ARLID |
cav_un_auth*0101212 |
| name1 |
Tichavský |
| name2 |
Petr |
| institution |
UTIA-B |
| full_dept (cz) |
Stochastická informatika |
| full_dept (eng) |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department (eng) |
SI |
| full_dept |
Department of Stochastic Informatics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0274170 |
| name1 |
Phan |
| name2 |
A. H. |
| country |
JP |
|
| source |
|
| cas_special |
| project |
| project_id |
GA22-11101S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0435406 |
|
| abstract
(eng) |
Tensor Chain (TC) decomposition represents a given tensor as a chain (circle) of order-3 tensors (wagons) connected through tensor contractions. In this paper, we show the link between the TC decomposition and a structured Tucker decompositions, and propose a variant of the Krylov-Levenberg-Marquardt optimization, tailored for this problem. Many extensions can be considered, here we only mention decomposition of tensor with missing entries, which enables the tensor completion. Performance of the proposed algorithm is demonstrated on tensor decomposition of the sampled Rosenbrock function. It can be better modeled both as TC and canonical polyadic (CP) decomposition, but with TC, the reconstruction is possible with a lower number of function values. |
| action |
| ARLID |
cav_un_auth*0452745 |
| name |
IEEE Statistical Signal Processing Workshop /22./ |
| dates |
20230702 |
| mrcbC20-s |
20230705 |
| place |
Hanoi |
| country |
VN |
|
| RIV |
BB |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20201 |
| reportyear |
2024 |
| num_of_auth |
2 |
| presentation_type |
PO |
| inst_support |
RVO:67985556 |
| permalink |
https://hdl.handle.net/11104/0344729 |
| confidential |
S |
| arlyear |
2023 |
| mrcbU14 |
SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
WOS |
| mrcbU56 |
374 kB |
| mrcbU63 |
cav_un_epca*0574035 Proceedings of the 22nd IEEE Statistical Signal Processing Workshop 978-1-6654-5244-1 557 561 Piscataway IEEE 2023 CFP23SAP-USB |
|