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Nonnegative PARAFAC2 : a flexible coupling approach. / Cohen, Jeremy E.; Bro, Rasmus.
Latent Variable Analysis and Signal Separation: 14th International Conference, LVA/ICA 2018, Proceedings. red. / Yannick Deville; Sharon Gannot; Russell Mason; Mark D. Plumbley; Dominic Ward. Springer, 2018. s. 89-98 (Lecture notes in computer science, Bind 10891).
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
Harvard
Cohen, JE
& Bro, R 2018,
Nonnegative PARAFAC2: a flexible coupling approach. i Y Deville, S Gannot, R Mason, MD Plumbley & D Ward (red),
Latent Variable Analysis and Signal Separation: 14th International Conference, LVA/ICA 2018, Proceedings. Springer, Lecture notes in computer science, bind 10891, s. 89-98, 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018, Guildford, Storbritannien,
02/07/2018.
https://doi.org/10.1007/978-3-319-93764-9_9APA
Cohen, J. E.
, & Bro, R. (2018).
Nonnegative PARAFAC2: a flexible coupling approach. I Y. Deville, S. Gannot, R. Mason, M. D. Plumbley, & D. Ward (red.),
Latent Variable Analysis and Signal Separation: 14th International Conference, LVA/ICA 2018, Proceedings (s. 89-98). Springer. Lecture notes in computer science Bind 10891
https://doi.org/10.1007/978-3-319-93764-9_9Vancouver
Cohen JE
, Bro R.
Nonnegative PARAFAC2: a flexible coupling approach. I Deville Y, Gannot S, Mason R, Plumbley MD, Ward D, red., Latent Variable Analysis and Signal Separation: 14th International Conference, LVA/ICA 2018, Proceedings. Springer. 2018. s. 89-98. (Lecture notes in computer science, Bind 10891).
https://doi.org/10.1007/978-3-319-93764-9_9Author
Cohen, Jeremy E. ; Bro, Rasmus. / Nonnegative PARAFAC2 : a flexible coupling approach. Latent Variable Analysis and Signal Separation: 14th International Conference, LVA/ICA 2018, Proceedings. red. / Yannick Deville ; Sharon Gannot ; Russell Mason ; Mark D. Plumbley ; Dominic Ward. Springer, 2018. s. 89-98 (Lecture notes in computer science, Bind 10891).
Bibtex
@inproceedings{2467c166f90042278a3a97ab519d8e80,
title = "Nonnegative PARAFAC2: a flexible coupling approach",
abstract = "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.",
keywords = "Flexible coupling, Nonnegativity constraints, PARAFAC2",
author = "Cohen, {Jeremy E.} and Rasmus Bro",
year = "2018",
doi = "10.1007/978-3-319-93764-9_9",
language = "English",
isbn = "978-3-319-93763-2",
series = "Lecture notes in computer science",
publisher = "Springer",
pages = "89--98",
editor = "Yannick Deville and Sharon Gannot and Russell Mason and Plumbley, {Mark D.} and Dominic Ward",
booktitle = "Latent Variable Analysis and Signal Separation",
address = "Switzerland",
note = "14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018 ; Conference date: 02-07-2018 Through 05-07-2018",
}
RIS
TY - GEN
T1 - Nonnegative PARAFAC2
T2 - 14th International Conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2018
AU - Cohen, Jeremy E.
AU - Bro, Rasmus
PY - 2018
Y1 - 2018
N2 - 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.
AB - 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.
KW - Flexible coupling
KW - Nonnegativity constraints
KW - PARAFAC2
U2 - 10.1007/978-3-319-93764-9_9
DO - 10.1007/978-3-319-93764-9_9
M3 - Article in proceedings
AN - SCOPUS:85048592779
SN - 978-3-319-93763-2
T3 - Lecture notes in computer science
SP - 89
EP - 98
BT - Latent Variable Analysis and Signal Separation
A2 - Deville, Yannick
A2 - Gannot, Sharon
A2 - Mason, Russell
A2 - Plumbley, Mark D.
A2 - Ward, Dominic
PB - Springer
Y2 - 2 July 2018 through 5 July 2018
ER -
