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2010 – 2019
- 2019
[j10]Nico Vervliet
, Otto Debals, Lieven De Lathauwer:
Exploiting Efficient Representations in Large-Scale Tensor Decompositions. SIAM J. Sci. Comput. 41(2): A789-A815 (2019)- [j9]Halandur Nagaraja Bharath, Otto Debals, Diana Maria Sima, Uwe Himmelreich, Lieven De Lathauwer, Sabine Van Huffel:
Tensor-Based Method for Residual Water Suppression in $^1$H Magnetic Resonance Spectroscopic Imaging. IEEE Trans. Biomed. Eng. 66(2): 584-594 (2019) - 2018
- [j8]Martijn Bousse, Nico Vervliet, Ignat Domanov, Otto Debals, Lieven De Lathauwer:
Linear systems with a canonical polyadic decomposition constrained solution: Algorithms and applications. Numer. Linear Algebra Appl. 25(6) (2018) - [j7]Frederik Van Eeghem, Otto Debals, Lieven De Lathauwer:
Tensor Similarity in Two Modes. IEEE Trans. Signal Process. 66(5): 1273-1285 (2018) - [j6]Frederik Van Eeghem, Otto Debals, Nico Vervliet, Lieven De Lathauwer:
Coupled and Incomplete Tensors in Blind System Identification. IEEE Trans. Signal Process. 66(23): 6137-6147 (2018) - 2017
- [b1]Otto Debals:
Tensorization and Applications in Blind Source Separation ; Tensorizatie met applicaties in blinde signaalscheiding. Katholieke Universiteit Leuven, Belgium, 2017 - [j5]Otto Debals, Marc Van Barel, Lieven De Lathauwer:
Nonnegative Matrix Factorization Using Nonnegative Polynomial Approximations. IEEE Signal Process. Lett. 24(7): 948-952 (2017) - [j4]Martijn Bousse, Otto Debals, Lieven De Lathauwer:
A Tensor-Based Method for Large-Scale Blind Source Separation Using Segmentation. IEEE Trans. Signal Process. 65(2): 346-358 (2017) - [j3]Martijn Bousse, Otto Debals, Lieven De Lathauwer:
Tensor-Based Large-Scale Blind System Identification Using Segmentation. IEEE Trans. Signal Process. 65(21): 5770-5784 (2017) - [c8]Martijn Bousse, Nico Vervliet, Otto Debals, Lieven De Lathauwer:
Face recognition as a kronecker product equation. CAMSAP 2017: 1-5 - [c7]Martijn Bousse, Griet Goovaerts, Nico Vervliet, Otto Debals, Sabine Van Huffel, Lieven De Lathauwer:
Irregular heartbeat classification using Kronecker Product Equations. EMBC 2017: 438-441 - 2016
- [j2]Otto Debals, Marc Van Barel, Lieven De Lathauwer:
Löwner-Based Blind Signal Separation of Rational Functions With Applications. IEEE Trans. Signal Process. 64(8): 1909-1918 (2016) - [c6]Nico Vervliet, Otto Debals, Lieven De Lathauwer:
Tensorlab 3.0 - Numerical optimization strategies for large-scale constrained and coupled matrix/tensor factorization. ACSSC 2016: 1733-1738 - [c5]Martijn Bousse, Otto Debals, Lieven De Lathauwer:
A tensor-based method for large-scale blind system identification using segmentation. EUSIPCO 2016: 2015-2019 - [c4]Xiao-Feng Gong, Qiu-Hua Lin, Otto Debals, Nico Vervliet, Lieven De Lathauwer:
Coupled rank-(Lm, Ln, •) block term decomposition by coupled block simultaneous generalized Schur decomposition. ICASSP 2016: 2554-2558 - 2015
- [c3]Martijn Bousse, Otto Debals, Lieven De Lathauwer:
A novel deterministic method for large-scale blind source separation. EUSIPCO 2015: 1890-1894 - [c2]Otto Debals, Lieven De Lathauwer:
Stochastic and Deterministic Tensorization for Blind Signal Separation. LVA/ICA 2015: 3-13 - [c1]Otto Debals, Marc Van Barel, Lieven De Lathauwer:
Blind signal separation of rational functions using Löwner-based tensorization. ICASSP 2015: 4145-4149 - 2014
- [j1]Nico Vervliet, Otto Debals, Laurent Sorber, Lieven De Lathauwer:
Breaking the Curse of Dimensionality Using Decompositions of Incomplete Tensors: Tensor-based scientific computing in big data analysis. IEEE Signal Process. Mag. 31(5): 71-79 (2014)
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