Large marginwavelet-based dictionary for signal classification. - Florian Yger; Alain Rakotomamonjy (ICASSP, 2010)

Selecting from an infinite set of features in SVM. - Rémi Flamary; Florian Yger; Alain Rakotomamonjy (ESANN, 2011)

A supervised strategy for deep kernel machine. - Florian Yger; Maxime Berar; Gilles Gasso; Alain Rakotomamonjy (ESANN, 2011)

Wavelet kernel learning. - Florian Yger; Alain Rakotomamonjy (Pattern Recognit., 2011)

Apprentissage de dictionnaires d'ondelettes vaste marge pour la classification de signaux et de textures. - Florian Yger; Alain Rakotomamonjy (Rev. d'Intelligence Artif., 2011)

Oblique principal subspace tracking on manifold. - Florian Yger; Maxime Berar; Gilles Gasso; Alain Rakotomamonjy (ICASSP, 2012)

Adaptive Canonical Correlation Analysis Based On Matrix Manifolds. - Florian Yger; Maxime Berar; Gilles Gasso; Alain Rakotomamonjy (ICML, 2012)

A review of kernels on covariance matrices for BCI applications. - Florian Yger (MLSP, 2013)

Learning with infinitely many features. - Alain Rakotomamonjy; Rémi Flamary; Florian Yger (Mach. Learn., 2013)

Challenge IEEE-ISBI/TCB : Application of Covariance matrices and wavelet marginals. - Florian Yger (CoRR, 2014)

Averaging covariance matrices for EEG signal classification based on the CSP: An empirical study. - Florian Yger; Fabien Lotte; Masashi Sugiyama (EUSIPCO, 2015)

Supervised LogEuclidean Metric Learning for Symmetric Positive Definite Matrices. - Florian Yger; Masashi Sugiyama (CoRR, 2015)

Importance-weighted covariance estimation for robust common spatial pattern. - Alessandro Balzi; Florian Yger; Masashi Sugiyama (Pattern Recognit. Lett., 2015)

Geometry-aware stationary subspace analysis. - Inbal Horev; Florian Yger; Masashi Sugiyama (ACML, 2016)

Multitask Principal Component Analysis. - Ikko Yamane; Florian Yger; Maxime Berar; Masashi Sugiyama (ACML, 2016)

Recognizing Art Style Automatically in Painting with Deep Learning. - Adrian Lecoutre; Benjamin Négrevergne; Florian Yger (ACML, 2017)

Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario. - Jill-Jênn Vie; Florian Yger; Ryan Lahfa; Basile Clement; Kévin Cocchi; Thomas Chalumeau; Hisashi Kashima (MANPU@ICDAR, 2017)

Online Learning of Acyclic Conditional Preference Networks from Noisy Data. - Fabien Labernia; Bruno Zanuttini; Brice Mayag; Florian Yger; Jamal Atif (ICDM, 2017)

Geometry-aware principal component analysis for symmetric positive definite matrices. - Inbal Horev; Florian Yger; Masashi Sugiyama (Mach. Learn., 2017)

Uplift Modeling from Separate Labels. - Ikko Yamane; Florian Yger; Jamal Atif; Masashi Sugiyama (NeurIPS, 2018)

Graph-based Clustering under Differential Privacy. - Rafael Pinot; Anne Morvan; Florian Yger; Cédric Gouy-Pailler; Jamal Atif (UAI, 2018)

Towards Adaptive Classification using Riemannian Geometry approaches in Brain-Computer Interfaces. - Satyam Kumar 005; Florian Yger; Fabien Lotte (BCI, 2019)

Theoretical evidence for adversarial robustness through randomization. - Rafael Pinot; Laurent Meunier; Alexandre Araujo; Hisashi Kashima; Florian Yger; Cédric Gouy-Pailler; Jamal Atif (NeurIPS, 2019)

Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family. - Rafael Pinot; Laurent Meunier; Alexandre Araujo; Hisashi Kashima; Florian Yger; Cédric Gouy-Pailler; Jamal Atif (CoRR, 2019)

Robust Neural Networks using Randomized Adversarial Training. - Alexandre Araujo; Rafael Pinot; Benjamin Négrevergne; Laurent Meunier; Yann Chevaleyre; Florian Yger; Jamal Atif (CoRR, 2019)

A unified view on differential privacy and robustness to adversarial examples. - Rafael Pinot; Florian Yger; Cédric Gouy-Pailler; Jamal Atif (CoRR, 2019)

Geodesically-convex optimization for averaging partially observed covariance matrices. - Florian Yger; Sylvain Chevallier; Quentin Barthélemy; Suvrit Sra (ACML, 2020)

Estimating Individual Treatment Effects through Causal Populations Identification. - Céline Beji; Eric Benhamou; Michaël Bon; Florian Yger; Jamal Atif (ESANN, 2020)

Fréchet Mean Computation in Graph Space through Projected Block Gradient Descent. - Nicolas Boria; Benjamin Négrevergne; Florian Yger (ESANN, 2020)

Explainability for Regression CNN in Fetal Head Circumference Estimation from Ultrasound Images. - Jing Zhang 086; Caroline Petitjean; Florian Yger; Samia Ainouz 001 (iMIMIC/MIL3ID/LABELS@MICCAI, 2020)

A Metric Learning Approach to Graph Edit Costs for Regression. - Linlin Jia; Benoit Gaüzère; Florian Yger; Paul Honeine (S+SSPR, 2020)

Estimating Individual Treatment Effects through Causal Populations Identification. - Céline Beji; Michaël Bon; Florian Yger; Jamal Atif (CoRR, 2020)

Riemannian Geometry on Connectivity for Clinical BCI. - Marie-Constance Corsi; Florian Yger; Sylvain Chevallier; Camille Noûs (ICASSP, 2021)

Subspace Oddity - Optimization on Product of Stiefel Manifolds for EEG Data. - Maria Sayu Yamamoto; Florian Yger; Sylvain Chevallier (ICASSP, 2021)

Mediated Uncoupled Learning: Learning Functions without Direct Input-output Correspondences. - Ikko Yamane; Junya Honda; Florian Yger; Masashi Sugiyama (ICML, 2021)

Graph Homomorphism Features: Why Not Sample? - Paul Beaujean; Florian Sikora; Florian Yger (PKDD/ECML Workshops (1), 2021)

Neural Maximum Independent Set. - Thomas Pontoizeau; Florian Sikora; Florian Yger; Tristan Cazenave (PKDD/ECML Workshops (1), 2021)

The Minimum Edit Arborescence Problem and Its Use in Compressing Graph Collections. - Lucas Gnecco; Nicolas Boria; Sébastien Bougleux; Florian Yger; David B. Blumenthal (SISAP, 2021)

Clinical BCI Challenge-WCCI2020: RIGOLETTO - RIemannian GeOmetry LEarning, applicaTion To cOnnectivity. - Marie-Constance Corsi; Florian Yger; Sylvain Chevallier; Camille Noûs (CoRR, 2021)

Approximation of dilation-based spatial relations to add structural constraints in neural networks. - Mateus Riva; Pietro Gori; Florian Yger; Roberto Marcondes Cesar Junior; Isabelle Bloch (CoRR, 2021)

Scaling up graph homomorphism for classification via sampling. - Paul Beaujean; Florian Sikora; Florian Yger (CoRR, 2021)

Template-Based Graph Clustering. - Mateus Riva; Florian Yger; Pietro Gori; Roberto M. Cesar Jr.; Isabelle Bloch (CoRR, 2021)

The Minimum Edit Arborescence Problem and Its Use in Compressing Graph Collections [Extended Version]. - Lucas Gnecco; Nicolas Boria; Sébastien Bougleux; Florian Yger; David B. Blumenthal (CoRR, 2021)

A new Sinkhorn algorithm with Deletion and Insertion operations. - Luc Brun; Benoit Gaüzère; Sébastien Bougleux; Florian Yger (CoRR, 2021)

Non parametric estimation of causal populations in a counterfactual scenario. - Céline Beji; Florian Yger; Jamal Atif (CoRR, 2021)

Truth-Tracking via Approval Voting: Size Matters. - Tahar Allouche; Jérôme Lang; Florian Yger (AAAI, 2022)

Class-distinctiveness-based frequency band selection on the Riemannian manifold for oscillatory activity-based BCIs: preliminary results. - Maria Sayu Yamamoto; Fabien Lotte; Florian Yger; Sylvain Chevallier (EMBC, 2022)

Challenges in anomaly and change point detection. - Madalina Olteanu; Fabrice Rossi; Florian Yger (ESANN, 2022)

Is the U-NET Directional-Relationship Aware? - Mateus Riva; Pietro Gori; Florian Yger; Isabelle Bloch (ICIP, 2022)

A differentiable approximation for the Linear Sum Assignment Problem with Edition. - Luc Brun; Benoit Gaüzère; Guillaume Renton; Sébastien Bougleux; Florian Yger (ICPR, 2022)

Multi-winner approval voting goes epistemic. - Tahar Allouche; Jérôme Lang; Florian Yger (UAI, 2022)

On the robustness of randomized classifiers to adversarial examples. - Rafael Pinot; Laurent Meunier; Florian Yger; Cédric Gouy-Pailler; Yann Chevaleyre; Jamal Atif (Mach. Learn., 2022)

Riemannian geometry for combining functional connectivity metrics and covariance in BCI. - Sylvain Chevallier; Marie-Constance Corsi; Florian Yger; Fabrizio de Vico Fallani (Softw. Impacts, 2022)

Functional Connectivity Ensemble Method to Enhance BCI Performance (FUCONE). - Marie-Constance Corsi; Sylvain Chevallier; Fabrizio de Vico Fallani; Florian Yger (IEEE Trans. Biomed. Eng., 2022)

Mediated Uncoupled Learning and Validation with Bregman Divergences: Loss Family with Maximal Generality. - Ikko Yamane; Yann Chevaleyre; Takashi Ishida 001; Florian Yger (AISTATS, 2023)

Temporal Sequences of EEG Covariance Matrices for Automated Sleep Stage Scoring with Attention Mechanisms. - Mathieu Seraphim; Paul Dequidt; Alexis Lechervy; Florian Yger; Luc Brun; Olivier Etard (CAIP (2), 2023)

The edge-preservation similarity for comparing rooted, unordered, node-labeled trees. - Nicolas Boria; Jana Kiederle; Florian Yger; David B. Blumenthal (Pattern Recognit. Lett., 2023)

Meta-survey on outlier and anomaly detection. - Madalina Olteanu; Fabrice Rossi; Florian Yger (Neurocomputing, 2023)

Structure-Preserving Transformers for Sequences of SPD Matrices. - Mathieu Seraphim; Alexis Lechervy; Florian Yger; Luc Brun; Olivier Etard (EUSIPCO, 2024)

Averaging Trajectories on the Manifold of Symmetric Positive Definite Matrices. - Thibault de Surrel; Florian Yger; Sylvain Chevallier; Fabien Lotte (EUSIPCO, 2024)

A Differentiable Approximation of the Graph Edit Distance. - Julia Wallnig; Luc Brun; Benoit Gaüzère; Sébastien Bougleux; Florian Yger; David B. Blumenthal (S+SSPR, 2024)

Automatic Classification of Sleep Stages from EEG Signals Using Riemannian Metrics and Transformer Networks. - Mathieu Seraphim; Alexis Lechervy; Florian Yger; Luc Brun; Olivier Etard (SN Comput. Sci., 2024)

Experimental Study of Binary Diffing Resilience on Obfuscated Programs. - Roxane Cohen; Robin David; Riccardo Mori; Florian Yger; Fabrice Rossi (DIMVA (1), 2025)

Geometry-Aware visualization of high dimensional Symmetric Positive Definite matrices. - Thibault de Surrel; Sylvain Chevallier; Fabien Lotte; Florian Yger (Trans. Mach. Learn. Res., 2025)

Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices. - Thibault de Surrel; Fabien Lotte; Sylvain Chevallier; Florian Yger (CoRR, 2025)

Identifying Obfuscated Code through Graph-Based Semantic Analysis of Binary Code. - Roxane Cohen; Robin David; Florian Yger; Fabrice Rossi (CoRR, 2025)

A probabilistic view on Riemannian machine learning models for SPD matrices. - Thibault de Surrel; Florian Yger; Fabien Lotte; Sylvain Chevallier (CoRR, 2025)