| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0363810 |
| utime |
20240111140759.6 |
| mtime |
20110913235959.9 |
| title
(primary) (eng) |
Damped Gauss-Newton algorithm for nonnegative Tucker Decomposition |
| specification |
| page_count |
4 s. |
| media_type |
CD ROM |
|
| serial |
| ARLID |
cav_un_epca*0363809 |
| ISBN |
978-1-4577-0568-7 |
| title
|
2011 IEEE Statistical Signal Processing Workshop (SSP) Proceedings |
| page_num |
669-672 |
| publisher |
| place |
Nice |
| name |
IEEE Signal Processing Society |
| year |
2011 |
|
|
| keyword |
nonnegative Tucker decomposition |
| keyword |
low-rank approximation |
| keyword |
face clustering |
| 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 |
1M0572 |
| agency |
GA MŠk |
| ARLID |
cav_un_auth*0001814 |
|
| project |
| project_id |
GA102/09/1278 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0253174 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
Algorithms based on alternating optimization for nonnegative Tucker decompositions (NTD) such as ALS, multiplicative least squares, HALS have been confirmed effective and efficient. However, those algorithms often converge very slowly. To this end, we propose a novel algorithm for NTD using the Levenberg-Marquardt technique with fast computation method to construct the approximate Hessian and gradient without building up the large-scale Jacobian. The proposed algorithm has been verified to overwhelmingly outperform “state-of-the-art” NTD algorithms for difficult benchmarks, and application of face clustering. |
| action |
| ARLID |
cav_un_auth*0274147 |
| name |
2011 IEEE Statistical Signal Processing Workshop (SSP) |
| place |
Nice |
| dates |
28.06.2011-30.06.2011 |
| country |
FR |
|
| reportyear |
2012 |
| RIV |
BB |
| num_of_auth |
3 |
| permalink |
http://hdl.handle.net/11104/0199466 |
| arlyear |
2011 |
| mrcbU56 |
496 kB |
| mrcbU63 |
cav_un_epca*0363809 2011 IEEE Statistical Signal Processing Workshop (SSP) Proceedings 978-1-4577-0568-7 669 672 Nice IEEE Signal Processing Society 2011 |
|