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Rémi Flamary
84
Documents
Researcher identifiers
remi-flamary
- Google Scholar : https://scholar.google.fr/citations?user=zDnwxFQAAAAJ&hl=fr
- IdRef : 188395008
-
0000-0002-4212-6627
Presentation
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Semi-relaxed Gromov-Wasserstein divergence for graphs classificationColloque GRETSI 2022 - XXVIIIème Colloque Francophone de Traitement du Signal et des Images, Sep 2022, Nancy, France
Conference papers
hal-03839524v1
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Multi-source Domain Adaptation via Weighted Joint Distributions Optimal TransportUncertainty in Artificial Intelligence (UAI), 2022, Eindhoven, Netherlands
Conference papers
hal-03832583v1
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Template based Graph Neural Network with Optimal Transport DistancesNeurIPS 2022 – 36th Conference on Neural Information Processing Systems, Nov 2022, New Orleans, United States
Conference papers
hal-03839517v1
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Unbalanced Optimal Transport through Non-negative Penalized Linear RegressionAdvances in Neural Information Processing Systems (NeurIPS), Dec 2021, Online, France
Conference papers
hal-03371489v1
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Online Graph Dictionary LearningICML 2021 - 38th International Conference on Machine Learning, Jul 2021, Virtual Conference, United States
Conference papers
hal-03140349v2
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Learning with minibatch Wasserstein : asymptotic and gradient propertiesAISTATS 2020 - 23nd International Conference on Artificial Intelligence and Statistics, Jun 2020, Palermo, Italy. pp.1-20
Conference papers
hal-02502329v1
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CO-Optimal TransportNeural Information Processing Systems (NeurIPS), Dec 2020, Online, Canada
Conference papers
hal-02972087v1
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Contextual Semantic InterpretabilityACCV (Asian Conference on Computer Vision), Dec 2020, Kyoto, France
Conference papers
hal-02972165v1
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Optimal Transport for Multi-source Domain Adaptation under Target Shift22nd International Conference on Artificial Intelligence and Statistics (AISTATS) 2019, Apr 2019, Naha, Japan
Conference papers
hal-02082874v1
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Sliced Gromov-WassersteinNeurIPS 2019 - Thirty-third Conference on Neural Information Processing Systems, Dec 2019, Vancouver, Canada
Conference papers
hal-02174309v1
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Unsupervised variable selection for kernel methods in systems biologyJournée Régionale de Bioinformatique et Biostatistique, Génopole Toulouse, Oct 2019, Toulouse, France
Conference papers
hal-02787253v1
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Optimal Transport for structured data with application on graphsICML 2019 - 36th International Conference on Machine Learning, Jun 2019, Long Beach, United States. pp.1-16
Conference papers
hal-02174322v1
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Large-Scale Optimal Transport and Mapping EstimationICLR 2018 - International Conference on Learning Representations, Apr 2018, Vancouver, Canada. pp.1-15
Conference papers
hal-01956354v1
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Learning Wasserstein EmbeddingsICLR 2018 - 6th International Conference on Learning Representations, Apr 2018, Vancouver, Canada. pp.1-13
Conference papers
hal-01956306v1
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DeepJDOT: Deep Joint Distribution Optimal Transport for Unsupervised Domain AdaptationECCV 2018 - 15th European Conference on Computer Vision, Sep 2018, Munich, Germany. pp.467-483, ⟨10.1007/978-3-030-01225-0_28⟩
Conference papers
hal-01956356v1
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Distributed Approach for Deblurring Large Images with Shift-Variant Blur2017 25th European Signal Processing Conference, Aug 2017, Kos Island, Greece. ⟨10.23919/EUSIPCO.2017.8081653⟩
Conference papers
hal-02365713v1
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Joint distribution optimal transportation for domain adaptationNIPS 2017, Dec 2017, Los Angeles, United States
Conference papers
hal-01620589v1
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Doubly compressed diffusion LMS over adaptive networks2016 50th Asilomar Conference on Signals, Systems and Computers, Nov 2016, Pacific Grove, France. pp.987-991, ⟨10.1109/ACSSC.2016.7869515⟩
Conference papers
hal-03633804v1
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Mapping Estimation for Discrete Optimal TransportNeural Information Processing System, Dec 2016, Barcelone, Spain
Conference papers
hal-01376970v1
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Supervised Planetary Unmixing with Optimal TransportWHISPERS 8th workshop on Hyperspectral image and Signal Processing: Evolution in Remote Sensing, Aug 2016, Los Angeles, United States
Conference papers
hal-01377236v1
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Optimal Transport for Data Fusion in Remote SensingIGARSS, Jul 2016, Beijing, China
Conference papers
hal-01377234v1
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Optimal spectral transportation with application to music transcriptionAdvances in Neural Information Processing Systems (NIPS), Dec 2016, Barcelona, Spain
Conference papers
hal-01377533v1
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Toward privacy-preserving diffusion strategies for adaptation and learning over networks2016 24th European Signal Processing Conference (EUSIPCO), Aug 2016, Budapest, France. pp.1513-1517, ⟨10.1109/EUSIPCO.2016.7760501⟩
Conference papers
hal-03633856v1
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Multitemporal classification without new labels: A solution with optimal transportMultitemp, Jul 2015, Annecy, France. ⟨10.1109/Multi-Temp.2015.7245773⟩
Conference papers
hal-01254329v1
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Importance sampling strategy for non-convex randomized block-coordinate descentIEEE INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING, Dec 2015, Cancun, Mexico. ⟨10.1109/CAMSAP.2015.7383796⟩
Conference papers
hal-01336588v1
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Optimal transport for Domain adaptationNIPS 2014, Workshop on Optimal Transport and Machine Learning, Dec 2014, Montréal, Canada
Conference papers
hal-01103073v1
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Optimal transport with Laplacian regularizationNIPS 2014, Workshop on Optimal Transport and Machine Learning, Dec 2014, Montréal, Canada
Conference papers
hal-01103076v1
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Active set strategy for high-dimensional non-convex sparse optimization problemsICASSP - IEEE International Conference on Acoustics Speech and Signal Processing, May 2014, Florence, Italy
Conference papers
hal-01025585v1
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Domain adaptation with regularized optimal transportECML/PKDD 2014, Sep 2014, Nancy, France. pp.1-16
Conference papers
hal-01018698v1
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Distributed image reconstruction for very large arrays in radio astronomySensor Array and Multichannel Signal Processing Workshop (SAM), 2014 IEEE 8th, Jun 2014, Coruna, Spain. ⟨10.1109/SAM.2014.6882424⟩
Conference papers
hal-01170722v1
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A group-lasso active set strategy for multiclass hyperspectral image classificationPhotogrammetric Computer Vision (PCV), Sep 2014, Zürich, Switzerland. pp.1--9
Conference papers
hal-01063450v1
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Large Scale Sparse Optimization for Object Detection in High Resolution ImagesMLSP - 24th IEEE Workshop on Machine Learning for Signal Processing, Sep 2014, Reims, France
Conference papers
hal-01066235v1
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Discovering relevant spatial filterbanks for VHR image classification21st International Conference on Pattern Recognition (ICPR 2012), Nov 2012, Tsukuba, Japan. pp.3212-3215
Conference papers
hal-00798589v1
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Selecting from an infinite set of features in SVMEuropean Symposium on Artificial Neural Networks, Apr 2011, Bruges, Belgium
Conference papers
hal-00626168v1
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Spoken WordCloud: Clustering Recurrent Patterns in SpeechInternational Workshop on Content-Based Multimedia Indexing, Jun 2011, Madrid, Spain
Conference papers
hal-00582799v1
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Handling uncertainties in SVM classificationIEEE Workshop on Statistical Signal Processing, Jun 2011, Nice, France
Conference papers
hal-00582789v2
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Learning spatial filters for multispectral image segmentation.Machine Learning for Signal Processing, Aug 2010, Kittila, Finland. pp.1-6
Conference papers
hal-00528923v1
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Large margin filtering for signal sequence labelingIEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2010, Mar 2010, Dallas, United States. pp.1974 - 1977, ⟨10.1109/ICASSP.2010.5495281⟩
Conference papers
hal-00497300v2
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Filtrage vaste marge pour l'étiquetage séquentiel à noyaux de signauxConférence Francophone sur l'Apprentissage Automatique, May 2010, Clermont Ferrand, France. 12p
Conference papers
hal-00497296v1
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Sélection de variables pour l'apprentissage simultanée de tâchesConfrénce D'Apprentissage (CAp), May 2009, Hammamet, France. pp.109-120
Conference papers
hal-00452332v1
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Variational Sequence Labelinghttp://mlsp2009.conwiz.dk/, Sep 2009, Grenoble, France. pp.1-6, ⟨10.1109/MLSP.2009.5306238⟩
Conference papers
hal-00493553v1
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Discrimination périodique à partir d’observations multi-temporellesGRETSI 2015 - XXVème Colloque francophone de traitement du signal et des images, Sep 2015, Lyon, France. , 4 p., 2015
Conference poster
hal-02799273v1
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Statistical Learning for BCIsBrain–Computer Interfaces 1: Foundations and Methods, John Wiley & Sons, Inc., 2016, ⟨10.1002/9781119144977.ch9⟩
Book sections
hal-02343066v1
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Generalized conditional gradient: analysis of convergence and applications[Research Report] LITIS; Lagrange; IRISA. 2015
Reports
hal-01217870v1
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Decoding finger movements from ECoG signals using switching linear models2009
Reports
hal-00601154v1
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Apprentissage statistique pour le signal: applications aux interfaces cerveau-machineMachine Learning [stat.ML]. Université de Rouen, 2011. Français. ⟨NNT : ⟩
Theses
tel-00687501v1
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Interfaces Cerveau-MachineDEA. 2011
Lectures
cel-00675138v1
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