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Nico Vervliet
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2020 – today
- 2024
- [j12]Ignat Domanov, Nico Vervliet, Eric Evert, Lieven De Lathauwer:
Decomposition of a Tensor into Multilinear Rank-\({(M_{{r}},N_{{r}},\cdot )}\) Terms. SIAM J. Matrix Anal. Appl. 45(3): 1310-1334 (2024) - 2023
- [j11]Stijn Hendrikx
, Raphaël Widdershoven
, Nico Vervliet
, Lieven De Lathauwer
:
Tensorlab+: A Case Study on Reproducibility in Tensor Research. Comput. Sci. Eng. 25(5): 6-13 (2023) - [c12]Eric Evert, Nico Vervliet, Ignat Domanov, Lieven De Lathauwer:
Uniqueness Result and Algebraic Algorithm for Decomposition into Multilinear Rank- $(M_{r}, N_{r}, \cdot)$ Terms and Joint Block Diagonalization. CAMSAP 2023: 206-210 - 2022
- [j10]Nithin Govindarajan, Nico Vervliet, Lieven De Lathauwer:
Regression and Classification With Spline-Based Separable Expansions. Frontiers Big Data 5: 688496 (2022) - 2021
- [j9]Michiel Vandecappelle
, Nico Vervliet
, Lieven De Lathauwer
:
Inexact Generalized Gauss-Newton for Scaling the Canonical Polyadic Decomposition With Non-Least-Squares Cost Functions. IEEE J. Sel. Top. Signal Process. 15(3): 491-505 (2021) - [j8]Simon Van Eyndhoven
, Patrick Dupont
, Simon Tousseyn
, Nico Vervliet
, Wim Van Paesschen
, Sabine Van Huffel, Borbála Hunyadi
:
Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI data. NeuroImage 228: 117652 (2021) - 2020
- [j7]Xiao Fu
, Nico Vervliet, Lieven De Lathauwer
, Kejun Huang
, Nicolas Gillis
:
Computing Large-Scale Matrix and Tensor Decomposition With Structured Factors: A Unified Nonconvex Optimization Perspective. IEEE Signal Process. Mag. 37(5): 78-94 (2020) - [j6]Michiel Vandecappelle
, Nico Vervliet
, Lieven De Lathauwer
:
A Second-Order Method for Fitting the Canonical Polyadic Decomposition With Non-Least-Squares Cost. IEEE Trans. Signal Process. 68: 4454-4465 (2020) - [c11]Nico Vervliet, Andreas Themelis
, Panagiotis Patrinos
, Lieven De Lathauwer:
A Quadratically Convergent Proximal Algorithm For Nonnegative Tensor Decomposition. EUSIPCO 2020: 1020-1024 - [i2]Simon Van Eyndhoven
, Patrick Dupont, Simon Tousseyn, Nico Vervliet, Wim Van Paesschen, Sabine Van Huffel, Borbála Hunyadi:
Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI data. CoRR abs/2004.14185 (2020) - [i1]Xiao Fu, Nico Vervliet, Lieven De Lathauwer, Kejun Huang, Nicolas Gillis:
Nonconvex Optimization Tools for Large-Scale Matrix and Tensor Decomposition with Structured Factors. CoRR abs/2006.08183 (2020)
2010 – 2019
- 2019
- [j5]Nico Vervliet
, Otto Debals, Lieven De Lathauwer
:
Exploiting Efficient Representations in Large-Scale Tensor Decompositions. SIAM J. Sci. Comput. 41(2): A789-A815 (2019) - [c10]Stijn Hendrikx
, Martijn Boussé
, Nico Vervliet, Lieven De Lathauwer:
Algebraic and Optimization Based Algorithms for Multivariate Regression Using Symmetric Tensor Decomposition. CAMSAP 2019: 475-479 - [c9]Nico Vervliet, Michiel Vandecappelle, Martijn Boussé
, Rob Zink, Lieven De Lathauwer:
Recent Numerical and Conceptual Advances for Tensor Decompositions - A Preview of Tensorlab 4.0. DSW 2019: 310-314 - [c8]Simon Van Eyndhoven
, Nico Vervliet, Lieven De Lathauwer, Sabine Van Huffel:
Identifying Stable Components of Matrix /Tensor Factorizations via Low-Rank Approximation of Inter-Factorization Similarity. EUSIPCO 2019: 1-5 - [c7]Michiel Vandecappelle, Nico Vervliet, Lieven De Lathauwer:
Rank-one Tensor Approximation with Beta-divergence Cost Functions. EUSIPCO 2019: 1-5 - 2018
- [j4]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) - [j3]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) - [c6]Michiel Vandecappelle, Martijn Bousse
, Nico Vervliet, Lieven De Lathauwer:
CPD Updating Using Low-Rank Weights. ICASSP 2018: 6368-6372 - 2017
- [c5]Martijn Bousse
, Nico Vervliet, Otto Debals, Lieven De Lathauwer:
Face recognition as a kronecker product equation. CAMSAP 2017: 1-5 - [c4]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 - [c3]Michiel Vandecappelle, Nico Vervliet, Lieven De Lathauwer:
Nonlinear least squares updating of the canonical polyadic decomposition. EUSIPCO 2017: 663-667 - 2016
- [j2]Nico Vervliet
, Lieven De Lathauwer:
A Randomized Block Sampling Approach to Canonical Polyadic Decomposition of Large-Scale Tensors. IEEE J. Sel. Top. Signal Process. 10(2): 284-295 (2016) - [c2]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 - [c1]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 - 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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last updated on 2024-08-17 23:42 CEST by the dblp team
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