Marc Castella
Publications
Publications
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Can GANs recover faults in electrical motor sensors?ICLR 2022 - International Conference on Learning Representations (ICLR ), Apr 2022, Virtual, France |
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Weight identification through global optimization in a new hysteretic neural network modelICASSP 2021 - 46th International Conference on Acoustics, Speech and Signal Processing, Jun 2021, Toronto (online), Canada. pp.5315-5319, ⟨10.1109/ICASSP39728.2021.9413383⟩ |
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Neural networks based speed-torque estimators for induction motors and performance metricsIECON 2020 - 46th Annual Conference of the IEEE Industrial Electronics Society, Oct 2020, Singapore, Singapore. pp.495-500, ⟨10.1109/IECON43393.2020.9255236⟩ |
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Globally optimizing owing to tensor decompositionEUSIPCO 2020 - 28th European Signal Processing Conference, Jan 2020, Amsterdam, Netherlands. pp.990-994, ⟨10.23919/Eusipco47968.2020.9287511⟩ |
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Modeling electrical motor dynamics using encoder-decoder with recurrent skip connectionAAAI 2020 - 34th AAAI conference on artificial intelligence, Feb 2020, New York, United States. pp.1387-1394 |
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Detecting the Rank of a Symmetric TensorEUSIPCO 2019 - 27th European Signal Processing Conference, Sep 2019, Coruña, Spain. pp.1-5 |
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A moment-based approach for guaranteed tensor decompositionICASSP 2020 - 45th International Conference on Acoustics, Speech and Signal Processing, May 2020, Barcelona, Spain. pp.3927-3931, ⟨10.1109/icassp40776.2020.9054186⟩ |
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Robust reconstruction with nonconvex subset constraintsMLSP 2020 - IEEE 30th international workshop on Machine Learning for Signal Processing, Sep 2020, Espoo (online), Finland. pp.1-6, ⟨10.1109/MLSP49062.2020.9231524⟩ |
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How to globally solve non-convex optimization problems involving an approximate ℓ 0 penalizationICASSP 2019 : IEEE International Conference on Acoustics, Speech and Signal Processing, May 2019, Brighton, United Kingdom. pp.5601-5605, ⟨10.1109/ICASSP.2019.8683692⟩ |
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Sparse signal reconstruction with a sign oracleSPARS 2019 - Signal Processing with Adaptive Sparse Structured Representations - Workshop, Jul 2019, Toulouse, France |
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Signal reconstruction from sub-sampled and nonlinearly distorted observationsEUSIPCO 2018: 26th European Signal Processing Conference, Sep 2018, Roma, Italy. pp.1970-1974, ⟨10.23919/EUSIPCO.2018.8553174⟩ |
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A global optimization approach for rational sparsity promoting criteriaEUSIPCO 2017 - 25th European Signal Processing Conference, Aug 2017, Kos Island, Greece. pp.156 - 160, ⟨10.23919/EUSIPCO.2017.8081188⟩ |
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Recovery of nonlinearly degraded sparse signals through rational optimizationSPARS 2017 - 6th Signal Processing with Adaptive Sparse Structured Representations workshop, Jun 2017, Lisbonne, Portugal. pp.1-2 |
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Optimization of a Geman-McClure like criterion for sparse signal deconvolutionCAMSAP 2015 : 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Dec 2015, Cancun, Mexico. pp.317-320, ⟨10.1109/CAMSAP.2015.7383798⟩ |
On a Practical Approach to Source Separation over Finite Fields for Network Coding ApplicationsIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2013, Vancouver, BC, Canada |
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An extension of the ICA model using latent variablesICASSP 2011 : 36th International Conference on Acoustics, Speech and Signal Processing, May 2011, Prague, Czech Republic. pp.3712 - 3715, ⟨10.1109/ICASSP.2011.5947157⟩ |
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Pairwise Markov model applied to unsupervised image separationSPPRA '11 : The Eighth IASTED International Conference on Signal Processing, Pattern Recognition, and Applications, Feb 2011, Innsbruck, Austria. ⟨10.2316/P.2011.721-044⟩ |
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Une extension avec variables latentes du modèle d'analyse en composantes indépendantesGRETSI 2011 : XXIIIe Colloque, Sep 2011, Bordeaux, France. pp.1 - 4 |
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A new method for kurtosis maximization and source separationICASSP 2010 : 35th International Conference on Acoustics, Speech, and Signal Processing , Mar 2010, Dallas, United States. pp.2670 - 2673, ⟨10.1109/ICASSP.2010.5496250⟩ |
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A new optimization method for reference-based quadratic contrast functions in a deflation scenarioICASSP 2009 : IEEE International Conference on Acoustics, Speech and Signal Processing, Apr 2009, Taipei, Taiwan. pp.3161 - 3164, ⟨10.1109/ICASSP.2009.4960295⟩ |
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Reference based contrast functions in a semi-blind contextICA 2009 : 8th International Conference on Independent Component Analysis and Signal Separation, Mar 2009, Paraty, Brazil. pp.9 - 16, ⟨10.1007/978-3-642-00599-2_2⟩ |
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Blind Separation of Instantaneous Mixtures of Dependent Sources7th International Conference on Independent Component Analysis and Signal Separation, Sep 2007, London, United Kingdom. pp.9-16 |
Source separation by quadratic contrast functions: a blind approach based on any higher-order statisticsIEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP'2005, Mar 2005, Philadelphia, USA, France. pp.569-572 |
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An iterative blind source separation method for convolutive mixtures of imagesProc. International Conference on Independent Component Analysis, ICA 04, Sep 2004, Granada, Spain, France. pp.922-929 |
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Blind MIMO detection of convolutively mixed CPM sourcesProc. European Signal and Image Processing Conference, EUSIPCO 04, 2004, Vienna, Austria, France. 10pp |
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A quadratic MISO contrast function for blind equalizationProc. of the IEEE Int. Conf. on Acoustics, Speech, and Signal Processing ICASSP 2004, May 2004, Montréal, Canada, France. pp.681-684 |
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Séparation aveugle d'un mélange convolutif de sources non linéaires par une approche hiérarchiqueGroupe de recherche et d'études du traitement du signal et des images (GRETSI'03), 2003, Paris, France, France. 10pp |
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Source separation of a class of non linear time seriesIEEE-Eurasip Workshop on Non Linear Signal and Image Processing (NSIP), Jun 2003, Grado, Italy, France. 10pp |
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New contrasts for blind separation of non iid sources in the convolutive caseProc. European Signal and Image Processing Conference, EUSIPCO 02, Vol.2, 2002, Toulouse, France, France. pp.107-110 |
A survey of kurtosis optimization schemes for MISO source separation and equalizationChatterjee; Amitava and Nobahari; Hadi and Siarry; Patrick. Advances in Heuristic Signal Processing and Applications, Springer, pp.183-217, 2013, 978-3-642-37879-9. ⟨10.1007/978-3-642-37880-5_9⟩ |
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Chapter 8 - Convolutive mixtures?. Handbook of Blind Source Separation, Independent Component Analysis and Applications, Elsevier, pp.281-324, 2011 |
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Mélanges convolutifsComon Pierre, Jutten Christian. Séparation de sources : concepts de base et analyse en composantes indépendantes, vol. 1, Hermès Science, Paris, pp.231-282, 2007 |
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Séparation de sources non linéaires dans le cas des mélanges convolutifsTraitement du signal et de l'image [eess.SP]. Université de Marne la Vallée, 2004. Français. ⟨NNT : ⟩ |