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Florian Yger
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2020 – today
- 2024
- [j11]Mathieu Seraphim
, Alexis Lechervy, Florian Yger, Luc Brun, Olivier Etard:
Automatic Classification of Sleep Stages from EEG Signals Using Riemannian Metrics and Transformer Networks. SN Comput. Sci. 5(7): 953 (2024) - [c38]Thibault de Surrel, Florian Yger, Sylvain Chevallier, Fabien Lotte:
Averaging Trajectories on the Manifold of Symmetric Positive Definite Matrices. EUSIPCO 2024: 1182-1186 - [c37]Mathieu Seraphim, Alexis Lechervy, Florian Yger, Luc Brun, Olivier Etard:
Structure-Preserving Transformers for Sequences of SPD Matrices. EUSIPCO 2024: 1451-1455 - 2023
- [j10]Madalina Olteanu, Fabrice Rossi
Meta-survey on outlier and anomaly detection. Neurocomputing 555: 126634 (2023) - [j9]Nicolas Boria, Jana Kiederle
The edge-preservation similarity for comparing rooted, unordered, node-labeled trees. Pattern Recognit. Lett. 167: 189-195 (2023) - [c36]Ikko Yamane, Yann Chevaleyre, Takashi Ishida, Florian Yger:
Mediated Uncoupled Learning and Validation with Bregman Divergences: Loss Family with Maximal Generality. AISTATS 2023: 4768-4801 - [c35]Mathieu Seraphim
Temporal Sequences of EEG Covariance Matrices for Automated Sleep Stage Scoring with Attention Mechanisms. CAIP (2) 2023: 67-76 - [i25]Mathieu Seraphim, Alexis Lechervy, Florian Yger, Luc Brun, Olivier Etard:
Structure-Preserving Transformers for Sequences of SPD Matrices. CoRR abs/2309.07579 (2023) - [i24]Madalina Olteanu, Fabrice Rossi, Florian Yger:
Meta-survey on outlier and anomaly detection. CoRR abs/2312.07101 (2023) - 2022
- [j8]Rafael Pinot
On the robustness of randomized classifiers to adversarial examples. Mach. Learn. 111(9): 3425-3457 (2022) - [j7]Sylvain Chevallier, Marie-Constance Corsi
Riemannian geometry for combining functional connectivity metrics and covariance in BCI. Softw. Impacts 12: 100254 (2022) - [j6]Marie-Constance Corsi
Functional Connectivity Ensemble Method to Enhance BCI Performance (FUCONE). IEEE Trans. Biomed. Eng. 69(9): 2826-2838 (2022) - [c34]Tahar Allouche, Jérôme Lang, Florian Yger:
Truth-Tracking via Approval Voting: Size Matters. AAAI 2022: 4768-4775 - [c33]Maria Sayu Yamamoto, Fabien Lotte, Florian Yger, Sylvain Chevallier:
Class-distinctiveness-based frequency band selection on the Riemannian manifold for oscillatory activity-based BCIs: preliminary results. EMBC 2022: 3690-3693 - [c32]Madalina Olteanu, Fabrice Rossi, Florian Yger:
Challenges in anomaly and change point detection. ESANN 2022 - [c31]Mateus Riva, Pietro Gori, Florian Yger, Isabelle Bloch:
Is the U-NET Directional-Relationship Aware? ICIP 2022: 3391-3395 - [c30]Luc Brun, Benoit Gaüzère, Guillaume Renton, Sébastien Bougleux
A differentiable approximation for the Linear Sum Assignment Problem with Edition. ICPR 2022: 3822-3828 - [c29]Tahar Allouche, Jérôme Lang, Florian Yger:
Multi-winner approval voting goes epistemic. UAI 2022: 75-84 - [i23]Tahar Allouche, Jérôme Lang, Florian Yger:
Multi-winner Approval Voting Goes Epistemic. CoRR abs/2201.06655 (2022) - [i22]Mateus Riva, Pietro Gori, Florian Yger, Isabelle Bloch:
Is the U-Net Directional-Relationship Aware? CoRR abs/2207.02574 (2022) - [i21]Madalina Olteanu, Fabrice Rossi, Florian Yger:
Challenges in anomaly and change point detection. CoRR abs/2212.13520 (2022) - 2021
- [c28]Marie-Constance Corsi
Riemannian Geometry on Connectivity for Clinical BCI. ICASSP 2021: 980-984 - [c27]Maria Sayu Yamamoto, Florian Yger, Sylvain Chevallier:
Subspace Oddity - Optimization on Product of Stiefel Manifolds for EEG Data. ICASSP 2021: 1080-1084 - [c26]Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama:
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences. ICML 2021: 11637-11647 - [c25]Paul Beaujean, Florian Sikora, Florian Yger:
Graph Homomorphism Features: Why Not Sample? PKDD/ECML Workshops (1) 2021: 216-222 - [c24]Thomas Pontoizeau, Florian Sikora, Florian Yger, Tristan Cazenave:
Neural Maximum Independent Set. PKDD/ECML Workshops (1) 2021: 223-237 - [c23]Lucas Gnecco
The Minimum Edit Arborescence Problem and Its Use in Compressing Graph Collections. SISAP 2021: 337-351 - [i20]Marie-Constance Corsi
Clinical BCI Challenge-WCCI2020: RIGOLETTO - RIemannian GeOmetry LEarning, applicaTion To cOnnectivity. CoRR abs/2102.06015 (2021) - [i19]Rafael Pinot, Laurent Meunier, Florian Yger, Cédric Gouy-Pailler, Yann Chevaleyre, Jamal Atif:
On the robustness of randomized classifiers to adversarial examples. CoRR abs/2102.10875 (2021) - [i18]Mateus Riva, Pietro Gori, Florian Yger, Roberto Marcondes Cesar Junior, Isabelle Bloch:
Approximation of dilation-based spatial relations to add structural constraints in neural networks. CoRR abs/2102.10923 (2021) - [i17]Paul Beaujean, Florian Sikora, Florian Yger:
Scaling up graph homomorphism for classification via sampling. CoRR abs/2104.04040 (2021) - [i16]Mateus Riva, Florian Yger, Pietro Gori, Roberto M. Cesar Jr., Isabelle Bloch:
Template-Based Graph Clustering. CoRR abs/2107.01994 (2021) - [i15]Ikko Yamane, Junya Honda, Florian Yger, Masashi Sugiyama:
Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences. CoRR abs/2107.08135 (2021) - [i14]Lucas Gnecco, Nicolas Boria, Sébastien Bougleux, Florian Yger, David B. Blumenthal:
The Minimum Edit Arborescence Problem and Its Use in Compressing Graph Collections [Extended Version]. CoRR abs/2107.14525 (2021) - [i13]Marie-Constance Corsi
Functional connectivity ensemble method to enhance BCI performance (FUCONE). CoRR abs/2111.03122 (2021) - [i12]Luc Brun, Benoit Gaüzère, Sébastien Bougleux, Florian Yger:
A new Sinkhorn algorithm with Deletion and Insertion operations. CoRR abs/2111.14565 (2021) - [i11]Céline Beji, Florian Yger, Jamal Atif:
Non parametric estimation of causal populations in a counterfactual scenario. CoRR abs/2112.04288 (2021) - [i10]Tahar Allouche, Jérôme Lang, Florian Yger:
Truth-tracking via Approval Voting: Size Matters. CoRR abs/2112.04387 (2021) - 2020
- [c22]Florian Yger, Sylvain Chevallier, Quentin Barthélemy, Suvrit Sra:
Geodesically-convex optimization for averaging partially observed covariance matrices. ACML 2020: 417-432 - [c21]Céline Beji, Eric Benhamou, Michaël Bon, Florian Yger, Jamal Atif:
Estimating Individual Treatment Effects through Causal Populations Identification. ESANN 2020: 43-48 - [c20]Nicolas Boria, Benjamin Négrevergne, Florian Yger:
Fréchet Mean Computation in Graph Space through Projected Block Gradient Descent. ESANN 2020: 193-198 - [c19]Jing Zhang, Caroline Petitjean, Florian Yger
Explainability for Regression CNN in Fetal Head Circumference Estimation from Ultrasound Images. iMIMIC/MIL3ID/LABELS@MICCAI 2020: 73-82 - [c18]Linlin Jia
A Metric Learning Approach to Graph Edit Costs for Regression. S+SSPR 2020: 238-247 - [i9]Céline Beji, Michaël Bon, Florian Yger, Jamal Atif:
Estimating Individual Treatment Effects through Causal Populations Identification. CoRR abs/2004.05013 (2020)
2010 – 2019
- 2019
- [c17]Satyam Kumar, Florian Yger, Fabien Lotte
Towards Adaptive Classification using Riemannian Geometry approaches in Brain-Computer Interfaces. BCI 2019: 1-6 - [c16]Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif:
Theoretical evidence for adversarial robustness through randomization. NeurIPS 2019: 11838-11848 - [i8]Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif:
Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family. CoRR abs/1902.01148 (2019) - [i7]Alexandre Araujo, Rafael Pinot, Benjamin Négrevergne, Laurent Meunier, Yann Chevaleyre, Florian Yger, Jamal Atif:
Robust Neural Networks using Randomized Adversarial Training. CoRR abs/1903.10219 (2019) - [i6]Rafael Pinot, Florian Yger, Cédric Gouy-Pailler, Jamal Atif:
A unified view on differential privacy and robustness to adversarial examples. CoRR abs/1906.07982 (2019) - 2018
- [c15]Ikko Yamane, Florian Yger, Jamal Atif, Masashi Sugiyama:
Uplift Modeling from Separate Labels. NeurIPS 2018: 9949-9959 - [c14]Rafael Pinot, Anne Morvan, Florian Yger, Cédric Gouy-Pailler, Jamal Atif:
Graph-based Clustering under Differential Privacy. UAI 2018: 329-338 - [i5]Rafael Pinot, Anne Morvan, Florian Yger
Graph-based Clustering under Differential Privacy. CoRR abs/1803.03831 (2018) - 2017
- [j5]Inbal Horev
Geometry-aware principal component analysis for symmetric positive definite matrices. Mach. Learn. 106(4): 493-522 (2017) - [c13]Adrian Lecoutre, Benjamin Négrevergne, Florian Yger:
Recognizing Art Style Automatically in Painting with Deep Learning. ACML 2017: 327-342 - [c12]Jill-Jênn Vie
Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario. MANPU@ICDAR 2017: 21-26 - [c11]Fabien Labernia, Bruno Zanuttini, Brice Mayag, Florian Yger
Online Learning of Acyclic Conditional Preference Networks from Noisy Data. ICDM 2017: 247-256 - [i4]Jill-Jênn Vie, Florian Yger, Ryan Lahfa, Basile Clement, Kévin Cocchi, Thomas Chalumeau, Hisashi Kashima:
Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario. CoRR abs/1709.01584 (2017) - 2016
- [c10]Ikko Yamane, Florian Yger, Maxime Berar, Masashi Sugiyama:
Multitask Principal Component Analysis. ACML 2016: 302-317 - [c9]Inbal Horev, Florian Yger, Masashi Sugiyama:
Geometry-aware stationary subspace analysis. ACML 2016: 430-444 - [i3]Inbal Horev, Florian Yger, Masashi Sugiyama:
Geometry-aware stationary subspace analysis. CoRR abs/1605.07785 (2016) - 2015
- [j4]Alessandro Balzi, Florian Yger, Masashi Sugiyama
Importance-weighted covariance estimation for robust common spatial pattern. Pattern Recognit. Lett. 68: 139-145 (2015) - [c8]Inbal Horev, Florian Yger, Masashi Sugiyama:
Geometry-Aware Principal Component Analysis for Symmetric Positive Definite Matrices. ACML 2015: 1-16 - [c7]Florian Yger, Fabien Lotte
Averaging covariance matrices for EEG signal classification based on the CSP: An empirical study. EUSIPCO 2015: 2721-2725 - [i2]Florian Yger, Masashi Sugiyama:
Supervised LogEuclidean Metric Learning for Symmetric Positive Definite Matrices. CoRR abs/1502.03505 (2015) - 2014
- [i1]Florian Yger:
Challenge IEEE-ISBI/TCB : Application of Covariance matrices and wavelet marginals. CoRR abs/1410.2663 (2014) - 2013
- [j3]Alain Rakotomamonjy, Rémi Flamary
Learning with infinitely many features. Mach. Learn. 91(1): 43-66 (2013) - [c6]Florian Yger:
A review of kernels on covariance matrices for BCI applications. MLSP 2013: 1-6 - 2012
- [c5]Florian Yger, Maxime Berar, Gilles Gasso, Alain Rakotomamonjy:
Oblique principal subspace tracking on manifold. ICASSP 2012: 2429-2432 - [c4]Florian Yger, Maxime Berar, Gilles Gasso, Alain Rakotomamonjy:
Adaptive Canonical Correlation Analysis Based On Matrix Manifolds. ICML 2012 - 2011
- [j2]Florian Yger, Alain Rakotomamonjy:
Wavelet kernel learning. Pattern Recognit. 44(10-11): 2614-2629 (2011) - [j1]Florian Yger, Alain Rakotomamonjy:
Apprentissage de dictionnaires d'ondelettes vaste marge pour la classification de signaux et de textures. Rev. d'Intelligence Artif. 25(3): 369-392 (2011) - [c3]Rémi Flamary, Florian Yger, Alain Rakotomamonjy:
Selecting from an infinite set of features in SVM. ESANN 2011 - [c2]Florian Yger, Maxime Berar, Gilles Gasso, Alain Rakotomamonjy:
A supervised strategy for deep kernel machine. ESANN 2011 - 2010
- [c1]Florian Yger, Alain Rakotomamonjy:
Large marginwavelet-based dictionary for signal classification. ICASSP 2010: 2182-2185
Coauthor Index
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