A4 Article in conference proceedings
Higher-order Nonnegative CANDECOMP/PARAFAC Tensor Decomposition Using Proximal Algorithm (2019)


Wang, D., Cong, F., & Ristaniemi, T. (2019). Higher-order Nonnegative CANDECOMP/PARAFAC Tensor Decomposition Using Proximal Algorithm. In ICASSP 2019 : Proceedings of the 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (pp. 3457-3461). IEEE. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing. https://doi.org/10.1109/ICASSP.2019.8683217


JYU authors or editors


Publication details

All authors or editorsWang, Deqing; Cong, Fengyu; Ristaniemi, Tapani

Parent publicationICASSP 2019 : Proceedings of the 2019 IEEE International Conference on Acoustics, Speech and Signal Processing

ISBN978-1-4799-8131-1

Journal or seriesProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing

ISSN1520-6149

eISSN2379-190X

Publication year2019

Pages range3457-3461

PublisherIEEE

Publication countryUnited States

Publication languageEnglish

DOIhttps://doi.org/10.1109/ICASSP.2019.8683217

Publication open accessNot open

Publication channel open access

Publication is parallel published (JYX)https://jyx.jyu.fi/handle/123456789/63614

Additional information2019 IEEE International Conference on Acoustics, Speech, and Signal Processing. 12-17 May 2019 Brighton, United Kingdom.


Keywordssignal processing

Free keywordstensor decomposition; nonnegative CAN-DECOMP/PARAFAC; proximal algorithm; block principal pivoting; alternating nonnegative least squares


Contributing organizations

Other organizations:


Ministry reportingYes

Reporting Year2019

JUFO rating1


Last updated on 2024-11-05 at 18:46