Nonnegative PARAFAC2: a flexible coupling approach
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Modeling variability in tensor decomposition methods is one of the challenges of source separation. One possible solution to account for variations from one data set to another, jointly analysed, is to resort to the PARAFAC2 model. However, so far imposing constraints on the mode with variability has not been possible. In the following manuscript, a relaxation of the PARAFAC2 model is introduced, that allows for imposing nonnegativity constraints on the varying mode. An algorithm to compute the proposed flexible PARAFAC2 model is derived, and its performance is studied on both synthetic and chemometrics data.
Original language | English |
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Title of host publication | Latent Variable Analysis and Signal Separation : 14th International Conference, LVA/ICA 2018, Proceedings |
Editors | Yannick Deville, Sharon Gannot, Russell Mason, Mark D. Plumbley, Dominic Ward |
Number of pages | 10 |
Publisher | Springer |
Publication date | 2018 |
Pages | 89-98 |
ISBN (Print) | 978-3-319-93763-2 |
ISBN (Electronic) | 978-3-319-93764-9 |
DOIs | |
Publication status | Published - 2018 |
Event | 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018 - Guildford, United Kingdom Duration: 2 Jul 2018 → 5 Jul 2018 |
Conference
Conference | 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018 |
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Land | United Kingdom |
By | Guildford |
Periode | 02/07/2018 → 05/07/2018 |
Series | Lecture notes in computer science |
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Volume | 10891 |
ISSN | 0302-9743 |
- Flexible coupling, Nonnegativity constraints, PARAFAC2
Research areas
Links
- https://arxiv.org/pdf/1802.05035.pdf
Submitted manuscript
ID: 212909143