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 editors: Wang, Deqing; Cong, Fengyu; Ristaniemi, Tapani

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

ISBN: 978-1-4799-8131-1

Journal or series: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing

ISSN: 1520-6149

eISSN: 2379-190X

Publication year: 2019

Pages range: 3457-3461

Publisher: IEEE

Publication country: United States

Publication language: English

DOI: https://doi.org/10.1109/ICASSP.2019.8683217

Publication open access: Not open

Publication channel open access:

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

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

Keywords: signal processing

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

Contributing organizations

Ministry reporting: Yes

Reporting Year: 2019

JUFO rating: 1