Damped Gauss-Newton algorithm for nonnegative Tucker Decomposition

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F11%3A00363810" target="_blank" >RIV/67985556:_____/11:00363810 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Damped Gauss-Newton algorithm for nonnegative Tucker Decomposition
Original language description
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.
Czech name
—
Czech description
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2011 IEEE Statistical Signal Processing Workshop (SSP) Proceedings
ISBN
978-1-4577-0568-7
ISSN
—
e-ISSN
—
Number of pages
4
Pages from-to
669-672
Publisher name
IEEE Signal Processing Society
Place of publication
Nice
Event location
Nice
Event date
Jun 28, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—

Similar results(10)