| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0447197 |
| utime |
20240111140907.2 |
| mtime |
20150925235959.9 |
| SCOPUS |
84944706004 |
| WOS |
000363785500004 |
| DOI |
10.1007/978-3-319-22482-4_4 |
| title
(primary) (eng) |
Rank Splitting for CANDECOMP/PARAFAC |
| specification |
| page_count |
10 s. |
| media_type |
C |
|
| serial |
| ARLID |
cav_un_epca*0447195 |
| ISBN |
978-3-319-22482-4 |
| ISSN |
0302-9743 |
| title
|
Latent Variable Analysis and Signal Separation |
| page_num |
31-40 |
| publisher |
| place |
Heidelberg |
| name |
Springer |
| year |
2015 |
|
| editor |
| name1 |
Vincent |
| name2 |
Emmanuel |
|
| editor |
|
| editor |
| name1 |
Koldovský |
| name2 |
Zbyněk |
|
| editor |
| name1 |
Tichavský |
| name2 |
Petr |
|
|
| keyword |
Canonical polyadic decomposition |
| keyword |
PARAFAC |
| keyword |
deflation |
| author
(primary) |
| ARLID |
cav_un_auth*0274170 |
| name1 |
Phan |
| name2 |
A. H. |
| country |
JP |
|
| author
|
| ARLID |
cav_un_auth*0101212 |
| name1 |
Tichavský |
| name2 |
Petr |
| full_dept (cz) |
Stochastická informatika |
| full_dept |
Department of Stochastic Informatics |
| department (cz) |
SI |
| department |
SI |
| institution |
UTIA-B |
| full_dept |
Department of Stochastic Informatics |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0274171 |
| name1 |
Cichocki |
| name2 |
A. |
| country |
JP |
|
| source |
|
| cas_special |
| project |
| project_id |
GA14-13713S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0303443 |
|
| abstract
(eng) |
CANDECOMP/PARAFAC (CP) approximates multiway data by a sum of rank-1 tensors. Our recent study has presented a method to rank-1 tensor deflation, i.e. sequential extraction of rank-1 tensor components. In this paper, we extend the method to block deflation problem. When at least two factor matrices have full column rank, one can extract two rank-1 tensors simultaneously, and rank of the data tensor is reduced by 2. For decomposition of order-3 tensors of size R×R×R and rank-R, the block deflation has a complexity of O(R^3) per iteration which is lower than the cost O(R^4) of the ALS algorithm for the overall CP decomposition. |
| action |
| ARLID |
cav_un_auth*0319419 |
| name |
Latent Variable Analysis and Signal Separation 12th International Conference, LVA/ICA 2015 |
| place |
Liberec |
| dates |
25.08.2015-28.08.2015 |
| country |
CZ |
|
| reportyear |
2016 |
| RIV |
BB |
| num_of_auth |
3 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0249578 |
| confidential |
S |
| mrcbT16-s |
0.329 |
| mrcbT16-4 |
Q2 |
| mrcbT16-E |
Q2 |
| arlyear |
2015 |
| mrcbU14 |
84944706004 SCOPUS |
| mrcbU34 |
000363785500004 WOS |
| mrcbU56 |
365 kB |
| mrcbU63 |
cav_un_epca*0447195 Latent Variable Analysis and Signal Separation 978-3-319-22482-4 0302-9743 31 40 Heidelberg Springer 2015 LNCS 9237 Lecture Notes in Computer Science |
| mrcbU67 |
Vincent Emmanuel 340 |
| mrcbU67 |
Yeredor Arie 340 |
| mrcbU67 |
Koldovský Zbyněk 340 |
| mrcbU67 |
Tichavský Petr 340 |
|