Journal articles
V. Gilet, G. Mabilleau, M. Loumaigne, L. Coic, R. Vitale, T. Oberlin, J. H. de M. Goulart, N. Dobigeon, C. Ruckebusch, and D. Rousseau. Superpixels meet essential spectra for fast Raman hyperspectral microimaging. Optics Express, 32:932–948, January 2024. [ http | pdf ]
L. Coic, R. Vitale, M. Moreau, D. Rousseau, J. H. de M. Goulart, N. Dobigeon, and C. Ruckebusch. Assessment of essential information in the Fourier domain to accelerate Raman hyperspectral microimaging. Analytical Chemistry, October 2023. [ http | pdf ]
A. Marmin, J. H. de M. Goulart and C. Févotte. Majorization-minimization for Sparse Nonnegative Matrix Factorization with the β-divergence. IEEE Transactions on Signal Processing, 71:1435–1447, April 2023. [ http | pdf ]
A. Marmin, J. H. de M. Goulart and C. Févotte. Joint Majorization-Minimization for Nonnegative Matrix Factorization with the β-divergence. Elsevier Signal Processing, 209:109048, August 2023 . [ http | pdf ]
J. H. de M. Goulart, R. Couillet and P. Comon. A Random Matrix Perspective on Random Tensors. Journal of Machine Learning Research, 23(264):1–36, Sep 2022. [ http | pdf ]
P. M. S. Burt and J. H. de M. Goulart. On the realization of impulse invariant low-rank Volterra kernels. IEEE Signal Processing Letters, 29:1492–1496, Jun 2022. [ http | pdf ]
V. Stergiopoulou, L. Calatroni, J. H. de M. Goulart, S. Schaub and L. Blanc-Féraud. COL0RME: Super-resolution microscopy based on sparse blinking/fluctuating fluorophore localization and intensity
estimation. Biological Imaging, 2(E1), Feb 2022. [ http | pdf ]
P. M. R. de Oliveira, J. H. de M. Goulart, C. A. R. Fernandes and V. Zarzoso. Blind source separation in persistent atrial fibrillation electrocardiograms using block-term tensor decomposition with Lowner constraints. IEEE Journal of Biomedical and Health Informatics, 26(4):1538–1548, Apr 2022. [ pdf ]
J. H. de M. Goulart, P. M. R. de Oliveira, R. C. Farias, V. Zarzoso and P. Comon. Alternating group lasso for block-term tensor decomposition with application to ECG source separation. IEEE Transactions on Signal Processing, 68(1):2682–2696, Dec 2020. [ http | .pdf ]
J. H. de M. Goulart and P. Comon. On the minimal ranks of matrix pencils and the existence of a best approximate block-term tensor decomposition. Linear Algebra and Its Applications, 561:161–186, 2019. [ bib | http | pdf ]
P. M. S. Burt and J. H. de M. Goulart. Efficient computation of bilinear approximations and Volterra models of nonlinear systems. IEEE Transactions on Signal Processing, 66(3):804–816, Feb 2018. [ bib | http | .pdf ]
J. H. de M. Goulart, A. Y. Kibangou, and G. Favier. Traffic data imputation via tensor completion based on soft thresholding of Tucker core. Elsevier Transportation Research Part C: Emerging Technologies, 85:348–362, 2017. [ bib ]
J. H. de M. Goulart and G. Favier. Low-rank tensor recovery using sequentially optimal modal projections in iterative hard thresholding (SeMPIHT). SIAM Journal on Scientific Computing, 39(3):A860–A889, 2017. [ bib | http | .pdf ]
J. H. de M. Goulart, M. Boizard, R. Boyer, G. Favier, and P. Comon. Tensor CP decomposition with structured factor matrices: Algorithms and performance. IEEE Journal of Selected Topics in Signal Processing, 10(4):757–769, 2016. [ bib | http | .pdf ]
J. H. de M. Goulart and G. Favier. An algebraic solution for the Candecomp/PARAFAC decomposition with circulant factors. SIAM Journal on Matrix Analysis and Applications, 35(4):1543–1562, 2014. [ bib | http | .pdf ]
J. H. de M. Goulart and P. M. S. Burt. Efficient kernel computation for Volterra filter structure evaluation. IEEE Signal Processing Letters, 19(3):135–138, 2012. [ bib | http | .pdf ]
Conference articles
H. Lebeau, M. E. A. Seddik and J. H. de M. Goulart. Performance gaps in multi-view clustering under the nested matrix-tensor model. In Proceedings of the 12th International Conference on Learning Representations (ICLR), Vienna, Austria, May 2024. (accepted) [ pdf ]
M. E. A. Seddik, M. Guillaud, A. Decurninge and J. H. de M. Goulart. On the accuracy of Hotelling-type asymmetric tensor deflation: a random tensor analysis. In Proceedings of the 2023 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Los Sueños, Costa Rica, December 2023. [ pdf ]
M. E. A. Seddik, J. H. de M. Goulart, M. Guillaud and A. Decurninge. Hotelling deflation on large symmetric spiked tensors. In Annales du XXIXème Colloque Francophone de Traitement du Signal et des Images (GRETSI), Grenoble, France, August-September 2023. (accepted) [ http | .pdf ]
J. H. de M. Goulart and P. M. S. Burt. Volterra kernels of bilinear systems have tensor train structure. In Proceedings of the 26th European Signal Processing Conference (EUSIPCO), Dublin, Ireland, August 2021. [ http | .pdf ]
V. Stergiopoulou, J. H. de M. Goulart, S. Schaub, L. Calatroni and L. Blanc-Féraud. COL0RME: COvariance-based l0 super-Resolution Microscopy with intensity Estimation. In Proceedings of International Symposium on Biomedical Imaging (ISBI), Nice, France, April 2021. [ http | .pdf ]
J. H. de M. Goulart, L. Blanc-Féraud, E. Debreuve and S. Schaub. A study on tensor and matrix models for super-resolution fluorescence microscopy. In Proceedings of the 2019 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Le Gosier, Guadeloupe, December 2019. [ http | .pdf ]
R. C. Farias, J. H. de M. Goulart, and P. Comon. Coherence constrained alternating least squares. In Proceedings of the 26th European Signal Processing Conference (EUSIPCO), Rome, Italy, 2018. [ bib | http | .pdf ]
J. H. de M. Goulart and G. Favier. A general iterative imputation scheme with feedback control for tensor completion (IFCTC). In XXVIème colloque GRETSI (GRETSI 2017), Juan-Les-Pins, France, September 2017. [ bib | http ]
J. H. de M. Goulart and P. Comon. A novel non-iterative algorithm for low-multilinear-rank tensor approximation. In Proceedings of the 25th European Signal Processing Conference (EUSIPCO), Kos Island, Greece, 2017. [ bib | http | .pdf ]
J. H. de M. Goulart, M. Boizard, R. Boyer, G. Favier, and P. Comon. Statistical efficiency of structured CPD estimation applied to Wiener-Hammerstein modeling. In Proceedings of the 23rd European Signal Processing Conference (EUSIPCO), pages 948–952, Nice, France, September 2015. [ bib | http | .pdf ]
J. H. de M. Goulart and G. Favier. An iterative hard thresholding algorithm with improved convergence for low-rank tensor recovery. In Proceedings of the 23rd European Signal Processing Conference (EUSIPCO), pages 1701–1705, Nice, France, September 2015. [ bib | http | .pdf ]
M. Boizard, J. H. de M. Goulart, R. Boyer, G. Favier, and P. Comon. Performance asymptotique d’estimateurs de modèles CP avec facteurs structurés. In XXVème colloque GRETSI (GRETSI 2015), Lyon, France, September 2015. [ bib | http | .pdf ]
P. M. S. Burt and J. H. de M. Goulart. Evaluating the potential of Volterra-PARAFAC IIR models. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 5745–5749. IEEE, May 2013. [ bib | http | .pdf ]
J. H. de M. Goulart, L. Silva, L. Souza, and T. M. Fontes. Automação de otinas odontológicas adotadas no tratamento de doenças periodontais. In V Workshop de Informática médica, Porto Alegre, Brazil, 2005. [ bib ]
J. C. dos Santos Jr, J. H. de M. Goulart, L. Silva, L. Souza, M. C. Cabral, and T. M. Fontes. Um sistema para triagem de pacientes com doenças periodontais. In IV Workshop de Informática médica, Brasília, Brazil, 2004. [ bib ]
PhD thesis and MSc dissertation
J. H. de M. Goulart. Estimation of structured tensor models and recovery of low-rank tensors. PhD thesis, I3S Laboratory, Université Côte D’Azur, Sophia-Antipolis, France, 2016. [ bib | pdf ]
J. H. de M. Goulart. Efficient derivation and use of reference Volterra filters in the evaluation of nonlinear formalisms. MSc dissertation, Escola Politécnica da Universidade de São Paulo, Brazil, 2012. (In portuguese) [ http | pdf ]
Book chapters
G. Favier and J. H. de M. Goulart. Matrix algebra. In Favier, G. (ed.), From Algebraic Structures to Tensors, Wiley-ISTE, 2020. [ http ]
Submitted papers and preprints
M. E. A. Seddik, M. Achab and J. H. de M. Goulart. A Nested Matrix-Tensor Model for Noisy Multi-view Clustering. Preprint arXiv:2305.19992, 2023. [ pdf ]
Reports and other documents
J. H. de M. Goulart and P. Comon. Non-iterative low-multilinear-rank tensor approximation with application to decomposition in rank-(1,L,L) terms. 2017. [ bib | http | .pdf ]