Yger Florian - CV

LAMSADE

Yger Florian

Maître de conférences

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Biographie

Florian Yger est maître de conférences à l'Université Paris-Dauphine et enseigne l'analyse de données et l'apprentissage statistique au sein du département MIDO. Il est membre du laboratoire LAMSADE (Laboratoire d’Analyse et de Modélisation des Systèmes pour l’Aide à la Décision) et plus particulièrement de l'équipe MILES (Machine Intelligence LEarning Systems) qui se concentre sur l'intelligence artificielle responsable et explicable. 

Il a obtenu un doctorant en informatique de l'Université de Rouen en Juin 2013 sous la direction du Pr Alain Rakotomamonjy et du Dr Maxime Berar. Puis, il a ensuite été postdoctorant au LITIS sur des problèmes d'apprentissage multi-tâches du projet ANR LeMOn.
Ensuite, il a obtenu un financement postdoctoral JSPS pour rejoindre le groupe du Pr. Masashi Sugiyama à l'Université de Tokyo de Février 2014 à Septembre 2015.

Il a effectué des contributions à l'apprentissage de représentations (à travers des réprésentations induites par des projections, des noyaux ou des réseaux de neurones) et a appliqué ces travaux aux traitements de signaux (notamment pour des signaux EEG) et d'images (notamment pour la reconnaisannce de styles dans des peintures).
Plus récemment, il se concentre sur l'apprentissage contre-factuel.

Il est membre de Prairie (PaRis Artificial Intelligence Research InstitutE) dont il détient une chaire Tremplin.

Publications

Articles

Olteanu M., Rossi F., Yger F. (2023), Meta-survey on outlier and anomaly detection, Neurocomputing, vol. 555, p. 126634

Corsi M-C., Chevallier S., De Vico Fallani F., Yger F. (2022), Functional connectivity ensemble method to enhance BCI performance (FUCONE), IEEE Transactions on Biomedical Engineering, vol. 69, n°9, p. 2826-2838

Pinot R., Meunier L., Yger F., Gouy-Pailler C., Chevaleyre Y., Atif J. (2022), On the robustness of randomized classifiers to adversarial examples, Machine Learning, vol. 111, n°9, p. 3425–3457

Chevallier S., Corsi M-C., Yger F., De Vico Fallani F. (2022), Riemannian geometry for combining functional connectivity metrics and covariance in BCI, Software impacts, vol. 12, p. 100254

Labernia F., Yger F., Mayag B., Atif J. (2018), Query-based learning of acyclic conditional preference networks from contradictory preferences, EURO Journal on Decision Processes, vol. 6, n°1-2, p. 39-59

Pauty J., Usuba R., Cheng I., Hespel L., Takahashi H., Kato K., Kobayashi M., Nakajima H., Lee E., Yger F., Soncin F., Matsunaga Y. (2018), A Vascular Endothelial Growth Factor-Dependent Sprouting Angiogenesis Assay Based on an In Vitro Human Blood Vessel Model for the Study of Anti-Angiogenic Drugs, EBioMedicine, vol. 27, p. 225-236

Lotte F., Bougrain L., Cichocki A., Clerc M., Congedo M., Rakotomamonjy A., Yger F. (2018), A Review of Classification Algorithms for EEG-based Brain-Computer Interfaces: A 10-year Update, Journal of Neural Engineering, vol. 15, n°3

Yger F., Berar M., Lotte F. (2017), Riemannian approaches in Brain-Computer Interfaces: a review, IEEE Transactions on Neural System and Rehabilitation Engineering, n°99

Spiecker genannt Döhmann I., Tambou O., Bernal P., Hu M., Molinaro C., Negre E., Sarlet I., Schertel Mendes L., Witzleb N., Yger F. (2016), The Regulation of Commercial Profiling – A Comparative Analysis, European Data Protection Law Review, vol. 2, n°4, p. 535-554

Horev I., Yger F., Sugiyama M. (2016), Geometry-aware principal component analysis for symmetric positive definite matrices, Machine Learning, p. 1-30

Balzi A., Yger F., Sugiyama M. (2015), Importance-weighted covariance estimation for robust common spatial pattern, Pattern Recognition Letters, vol. 68, p. 139-145

Chapitres d'ouvrage

Chevallier S., Kalunga E., Barthélemy Q., Yger F. (2018), Riemannian Classification for SSVEP-Based BCI: Offline versus Online Implementations, in Chang S. Nam, Anton Nijholt, Fabien Lotte, Brain-Computer Interfaces Handbook : Technological and Theoretical Advances, London: CRC Press, Taylor & Francis, p. 372-398

Communications avec actes

Yamane I., Chevaleyre Y., Ishida T., Yger F. (2023), Mediated Uncoupled Learning and Validation with Bregman Divergences: Loss Family with Maximal Generality, in Francisco Ruiz ; Jennifer Dy ; Jan-Willem van de Meent, Proceedings of Machine Learning Research (PMLR)

Seraphim M., Dequidt P., Lechervy A., Yger F., Brun L., Etard O. (2023), Temporal Sequences of EEG Covariance Matrices for Automated Sleep Stage Scoring with Attention Mechanisms, in Nicolas Tsapatsoulis, Andreas Lanitis, Marios Pattichis, Constantinos Pattichis, Christos Kyrkou ; Efthyvoulos Kyriacou ; Zenonas Theodosiou ; Andreas Panayides, Berlin Heidelberg, Springer International Publishing, 67-76 p.

Pontoizeau T., Sikora F., Yger F., Cazenave T. (2022), Neural Maximum Independent Set, in , elsevier, Berlin Heidelberg, Springer International Publishing, 223–237 p.

BEAUJEAN P., Sikora F., Yger F. (2022), Graph Homomorphism Features: Why Not Sample?, in , Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Berlin Heidelberg, Springer International Publishing, 216–222 p.

Yamamoto M., Lotte F., Yger F., Chevallier S. (2022), Class-distinctiveness-based frequency band selection on the Riemannian manifold for oscillatory activity-based BCIs: preliminary results, in , Piscataway, NJ, IEEE - Institute of Electrical and Electronics Engineers

Riva M., Gori P., Yger F., Bloch I. (2022), Le Réseau U-Net Exploite-t-il des Relations Directionnelles Entre Objets pour les Segmenter et les Reconnaître ?, in , elsevier, Groupe de Recherche et d'Etudes de Traitement du Signal et des Images (GRETSI)

Allouche T., Lang J., Yger F. (2022), Truth-Tracking via Approval Voting: Size Matters, in , elsevier, Palo Alto (USA), AAAI Press, 4768-4775 p.

Corsi M-C., Yger F., Chevallier S., Noûs C. (2021), Riemannian Geometry on Connectivity for Clinical BCI, in , Piscataway, NJ, IEEE - Institute of Electrical and Electronics Engineers

Jia L., Gaüzère B., Yger F., Honeine P. (2021), A Metric Learning Approach to Graph Edit Costs for Regression, in Andrea Torsello, Luca Rossi, Marcello Pelillo, Springer, 238-247 p.

Zhang J., Petitjean C., Yger F., Ainouz S. (2020), Explainability for regression CNN in fetal head circumference estimation from ultrasound images, in Jaime Cardoso, Hien Van Nguyen, Nicholas Heller, Workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI 2020, Springer, 73-82 p.

Kumar S., Yger F., Lotte F. (2019), Towards Adaptive Classification using Riemannian Geometry approaches in Brain-Computer Interfaces, in Seong-Whan Lee, Klaus-Robert Müller, 2019 7th International Winter Conference on Brain-Computer Interface (BCI), Piscataway, NJ, IEEE - Institute of Electrical and Electronics Engineers

Pinot R., Morvan A., Yger F., Gouy-Pailler C., Atif J. (2018), Graph-based Clustering under Differential Privacy, in Amir Globerson; Ricardo Silva, Uncertainty in Artificial Intelligence (UAI) - Proceedings of the Thirty-Fourth Conference (2018), August 6-10, 2018, Monterey, California, USA, AUAI Press, 329-338 p.

Yamane I., Yger F., Atif J., Sugiyama M. (2018), Uplift Modeling from Separate Labels, in S. Bengio; H. Wallach; H. Larochelle; K. Grauman; N. Cesa-Bianchi; R. Garnett, Advances in Neural Information Processing Systems 31 (NIPS 2018), Neural Information Processing Systems Foundation, Inc., 9927--9937 p.

Lecoutre A., Negrevergne B., Yger F. (2017), Recognizing Art Style Automatically in painting with deep learning, in Yung-Kyun Noh, Min-Ling Zhang, Proceedings of the 9th Asian Conference on Machine Learning (ACML 2017), IEEE - Institute of Electrical and Electronics Engineers, 327-342 p.

Vie J-J., Yger F., Lahfa R., Clement B., Cocchi K., Chalumeau T., Kashima H. (2017), Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario, in Jean-Marc Ogier, Utpal Garain, Apostolos Antonacopoulos, 14th IAPR International Conference on Document Analysis and Recognition (ICDAR 2017), 2nd International Workshop on coMics ANalysis, Processing and Understanding (MANPU 2017), Kyoto, IEEE - Institute of Electrical and Electronics Engineers

Labernia F., Zanuttini B., Mayag B., Yger F., Atif J. (2017), Online learning of acyclic conditional preference networks from noisy data, in George Karypis, Lucio Miele, Proceedings of the IEEE International Conference on Data Mining (ICDM 2017), Piscataway, NJ, IEEE - Institute of Electrical and Electronics Engineers

Labernia F., Yger F., Mayag B., Atif J. (2016), Query-based learning of acyclic conditional preference networks from noisy data, in Róbert Busa-Fekete, Eyke Hüllermeier, Vincent Mousseau, Karlson Pfannschmidt, From Multiple Criteria Decision Aid to Preference Learning : Proceedings of the DA2PL'2016 EURO Mini Conference, Paderborn, Paderborn University, 6 p.

Horev I., Yger F., Sugiyama M. (2016), Geometry-aware stationary subspace analysis, in Robert J. Durrant, Kee-Eung Kim, Proceedings of The 8th Asian Conference on Machine Learning (ACML 2016), IEEE - Institute of Electrical and Electronics Engineers, 430-444 p.

Yamane I., Yger F., Berar M., Sugiyama M. (2016), Multitask Principal Component Analysis, in Robert J. Durrant, Kee-Eung Kim, Proceedings of The 8th Asian Conference on Machine Learning (ACML 2016), IEEE - Institute of Electrical and Electronics Engineers, 302-317 p.

Horev I., Yger F., Sugiyama M. (2015), Geometry-Aware Principal Component Analysis for Symmetric Positive Definite Matrices, in Geoffrey Holmes, Tie-Yan Liu, Proceedings of 7th Asian Conference on Machine Learning (ACML2015), IEEE - Institute of Electrical and Electronics Engineers, 1-16 p.

Yger F., Lotte F., Sugiyama M. (2015), Averaging covariance matrices for EEG signal classification based on the CSP: an empirical study, in , 23rd European Signal Processing Conference (EUSIPCO 2015), IEEE - Institute of Electrical and Electronics Engineers, 2721-2725 p.

Communications sans actes

Corsi M-C., Chevallier S., De Vico Fallani F., Yger F. (2023), Ensemble of Riemannian Classifiers for Multimodal Data: FUCONE Approach for M/EEG Data, IEEE International Symposium on Biomedical Imaging (ISBI) 2023, Cartagena de Indias, Colombie

Frateur R., Chevallier S., Yger F., Corsi M-C. (2023), Dimensionality Reduction and Frequency Bin Optimization To Improve a Riemannian-based Classification Pipeline, Journées CORTICO 2023 (COllectif pour la Recherche Transdisciplinaire sur les Interfaces Cerveau-Ordinateur), Paris, France

Corsi M-C., Chevallier S., De Vico Fallani F., Yger F. (2023), Ensemble of Riemannian classifiers for multimodal data: FUCONE approach for M/EEG data, 10th International BCI Meeting, Bruxelles, Belgique

Aristimunha B., Camargo R., Pinaya W., Yger F., Corsi M-C., Chevallier S. (2023), CONCERTO: Coherence & Functional Connectivity Graph Network, Journées CORTICO 2023 (COllectif pour la Recherche Transdisciplinaire sur les Interfaces Cerveau-Ordinateur), Paris, France

Seraphim M., Dequidt P., Lechervy A., Yger F., Brun L., Etard O. (2023), Analyse automatique de l'état de sommeil sur données EEG par utilisation de Transformers et de matrices de covariance, 19ème Colloque ORASIS (ORASIS 2023) : journées francophones des jeunes chercheurs en vision par ordinateur, Carqueiranne, France

Brun L., Gaüzère B., Renton G., Bougleux S., Yger F. (2022), A differentiable approximation for the Linear Sum Assignment Problem with Edition, 26th International Conference on Pattern Recognition (ICPR), Montréal, France

Riva M., Gori P., Yger F., Bloch I. (2022), Is the U-NET directional-relationship aware?, IEEE International Conference on Image Processing (ICIP 2022), Bordeaux, France

Olteanu M., Rossi F., Yger F. (2022), Challenges in anomaly and change point detection, 30th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2022), Bruges, Belgique

Corsi M-C., Chevallier S., Barthélemy Q., Hoxha I., Yger F. (2021), Ensemble learning based on functional connectivity and Riemannian geometry for robust workload estimation, Neuroergonomics conference 2021, Allemagne

Cohen R., Yger F., Rossi F. (2021), Adding semantic to level-up graph-based Android malware detection, The 10th International Conference on Complex Networks and their Applications (Complex Networks 2021), Madrid, Espagne

Yger F., Chevallier S., Barthélemy Q., Sra S. (2020), Geodesically-convex optimization for averaging partially observed covariance matrices, Proceedings of the Asian Conference on Machine Learning (ACML), Bangkok, ThaÏlande

Riva M., Yger F., Gori P., Cesar R., Bloch I. (2020), Template-Based Graph Clustering, ECML-PKDD, Workshop on Graph Embedding and Minin (GEM), Ghent, Belgique

Beji C., Benhamou É., Bon M., Yger F., Atif J. (2020), Estimating Individual Treatment Effects throughCausal Populations Identification, 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2020), Brugges, Belgique

Boria N., Negrevergne B., Yger F. (2020), Fréchet Mean Computation in Graph Space through Projected Block Gradient Descent, 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2020), Bruges, France

Chevallier S., Corsi M-C., Yger F., Noûs C. (2020), Extending Riemannian Brain-Computer Interface to Functional Connectivity Estimators, IROS Workshop on Bringing geometric methods to robot learning, optimization and control, Las Vegas, NV / Virtual, États-Unis

Pinot R., Yger F., Gouy-Pailler C., Atif J. (2019), A unified view on differential privacy and robustness to adversarial examples, Workshop on Machine Learning for CyberSecurity at ECMLPKDD 2019, Wurzburg, Allemagne

Rapports

Corsi M-C., Yger F., Chevallier S., Noûs C. (2021), Clinical BCI Challenge-WCCI2020: RIGOLETTO -- RIemannian GeOmetry LEarning, applicaTion To cOnnectivity, Preprint Lamsade

Brun L., Gaüzère B., Bougleux S., Yger F. (2021), A new Sinkhorn algorithm with Deletion and Insertion operations, Preprint Lamsade

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