Tensorlab 3.0 N Vervliet, O Debals, L Sorber, M Van Barel, L De Lathauwer available online, URL: www. tensorlab. net, 2016 | 279 | 2016 |
Breaking the Curse of Dimensionality using Decompositions of Incomplete Tensors N Vervliet, O Debals, L Sorber, L De Lathauwer | 208* | |
A tensor-based method for large-scale blind source separation using segmentation M Bousse, O Debals, L De Lathauwer IEEE Transactions on Signal Processing 65 (2), 346-358, 2016 | 130 | 2016 |
Tensorlab 3.0—Numerical optimization strategies for large-scale constrained and coupled matrix/tensor factorization N Vervliet, O Debals, L De Lathauwer 2016 50th Asilomar Conference on Signals, Systems and Computers, 1733-1738, 2016 | 110 | 2016 |
Löwner-based Blind Signal Separation of Rational Functions with Applications O Debals, L De Lathauwer Department of Electrical Engineering (ESAT), KU Leuven, ESAT-STADIUS …, 2015 | 59 | 2015 |
Linear systems with a canonical polyadic decomposition constrained solution: Algorithms and applications M Boussé, N Vervliet, I Domanov, O Debals, L De Lathauwer Numerical Linear Algebra with Applications 25 (6), e2190, 2018 | 43 | 2018 |
Stochastic and deterministic tensorization for blind signal separation O Debals, L De Lathauwer International Conference on Latent Variable Analysis and Signal Separation, 3-13, 2015 | 43 | 2015 |
Tensor-based large-scale blind system identification using segmentation M Boussé, O Debals, L De Lathauwer IEEE Transactions on Signal Processing 65 (21), 5770-5784, 2017 | 32 | 2017 |
Irregular heartbeat classification using Kronecker product equations M Boussé, G Goovaerts, N Vervliet, O Debals, S Van Huffel, ... 2017 39th Annual International Conference of the IEEE Engineering in …, 2017 | 26 | 2017 |
Canonical polyadic decomposition of incomplete tensors with linearly constrained factors N Vervliet, O Debals, L De Lathauwer Technical Report 16–172, ESAT-STADIUS, KU Leuven, Leuven, Belgium, 2017 | 23 | 2017 |
Coupled rank-(Lm, Ln, •) block term decomposition by coupled block simultaneous generalized Schur decomposition XF Gong, QH Lin, O Debals, N Vervliet, L De Lathauwer Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International …, 2016 | 10 | 2016 |
A novel deterministic method for large-scale blind source separation M Boussé, O Debals, L De Lathauwer | 8 | 2015 |
Blind Signal Separation of Rational Functions using Löwner-based Tensorization O Debals, M Van Barel, L De Lathauwer Department of Electrical Engineering (ESAT), KU Leuven, ESAT-STADIUS …, 2014 | 8 | 2014 |
Sum-of-Exponentials Modeling and Common Dynamics Estimation Using Tensorlab I Markovsky, O Debals, L De Lathauwer | 5* | |
A tensor-based method for large-scale blind system identification using segmentation M Boussé, O Debals, L De Lathauwer Signal Processing Conference (EUSIPCO), 2016 24th European, 2015-2019, 2016 | 4 | 2016 |
Tensor computations using Tensorlab O Debals, F Van Eeghem, N Vervliet, L De Lathauwer | 3 | 2015 |
Kronecker product equations and applications M Boussé, N Vervliet, O Debals, L De Lathauwer 5th Workshop on Matrix Equations and Tensor Techniques, presentation, 2015 | | 2015 |
A survey on stochastic and deterministic tensorization for blind signal separation O Debals, L De Lathauwer 34th Benelux Meeting on Systems and Control, 1-1, 2015 | | 2015 |
A tensor-based framework for blind identification of linear MIMO FIR systems F Van Eeghem, O Debals, L De Lathauwer 34th Benelux Meeting on Systems and Control, 1-1, 2015 | | 2015 |
Tensor-based algorithms for the analysis of data similarity in a blind system identification context F Van Eeghem, O Debals, L De Lathauwer Workshop on data-driven modeling methods and applications, 1-1, 2014 | | 2014 |