Amaury Habrard

152 papers A* 15A 4B 14Misc 2Journal 75Unranked 40

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Interpretable Reinforcement Learning for Load Balancing using Kolmogorov-Arnold Networks. CCNC Kamal Singh, Sami Marouani, Ahmad Al Sheikh, Pham Tran Anh Quang, Amaury Habrard
2026	J	`jnl`	PAC-Bayesian Generalization Guarantees for Fairness on Stochastic and Deterministic Classifiers. CoRR Julien Bastian, Benjamin Leblanc, Pascal Germain, Amaury Habrard, Christine Largeron, Guillaume Metzler, Emilie Morvant, Paul Viallard
2025	A*	`conf`	A Bregman Proximal Viewpoint on Neural Operators. ICML Abdel-Rahim Mezidi, Jordan Patracone, Saverio Salzo, Amaury Habrard, Massimiliano Pontil, Rémi Emonet, Marc Sebban
2025	—	`conf`	Contextual Hypernetwork for Adaptive Prediction of Laser-Induced Colors on Quasi-random Plasmonic Metasurfaces. ECML/PKDD (8) Thibault Girardin, Nathalie Destouches, Amaury Habrard
2025	J	`jnl`	From GNNs to Symbolic Surrogates via Kolmogorov-Arnold Networks for Delay Prediction. CoRR Sami Marouani, Kamal Singh, Baptiste Jeudy, Amaury Habrard
2025	J	`jnl`	Interpretable Reinforcement Learning for Load Balancing using Kolmogorov-Arnold Networks. CoRR Kamal Singh, Sami Marouani, Ahmad Al Sheikh, Pham Tran Anh Quang, Amaury Habrard
2025	J	`jnl`	Méthode de quadrature pour les PINNs fondée théoriquement sur la hessienne des résiduels. CoRR Antoine Caradot, Rémi Emonet, Amaury Habrard, Abdel-Rahim Mezidi, Marc Sebban
2025	—	`conf`	Provably Accurate Adaptive Sampling for Collocation Points in Physics-Informed Neural Networks. ECML/PKDD (5) Antoine Caradot, Rémi Emonet, Amaury Habrard, Abdel-Rahim Mezidi, Marc Sebban
2025	J	`jnl`	Provably accurate adaptive sampling for collocation points in physics-informed neural networks. CoRR Antoine Caradot, Rémi Emonet, Amaury Habrard, Abdel-Rahim Mezidi, Marc Sebban
2024	—	`conf`	A Theoretically Grounded Extension of Universal Attacks from the Attacker's Viewpoint. ECML/PKDD (4) Jordan Patracone, Paul Viallard, Emilie Morvant, Gilles Gasso, Amaury Habrard, Stéphane Canu
2024	J	`jnl`	A general framework for the practical disintegration of PAC-Bayesian bounds. Mach. Learn. Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
2024	B	`conf`	Advanced Traffic Engineering in WAN Using Graph Attention Networks. WiMob Sami Marouani, Kamal Singh, Baptiste Jeudy, Abbas Bradai, Amaury Habrard
2024	—	`conf`	Approximation Error of Sobolev Regular Functions with Tanh Neural Networks: Theoretical Impact on PINNs. ECML/PKDD (4) Benjamin Girault, Rémi Emonet, Amaury Habrard, Jordan Patracone, Marc Sebban
2024	B	`conf`	Generative shape deformation with optimal transport using learned transformations. IJCNN Jorge Azorín López, Marc Sebban, Nahuel E. Garcia-D'Urso, Amaury Habrard, Andrés Fuster Guilló
2024	A	`conf`	Length independent PAC-Bayes bounds for Simple RNNs. AISTATS Volodimir Mitarchuk, Clara Lacroce, Rémi Eyraud, Rémi Emonet, Amaury Habrard, Guillaume Rabusseau
2024	A	`conf`	Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. AISTATS Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi
2024	J	`jnl`	Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. CoRR Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi
2024	J	`jnl`	On the theoretical limit of gradient descent for Simple Recurrent Neural Networks with finite precision. Trans. Mach. Learn. Res. Volodimir Mitarchuk, Rémi Emonet, Rémi Eyraud, Amaury Habrard
2024	J	`jnl`	Scoring the predictions: a way to improve profiling side-channel attacks. IACR Cryptol. ePrint Arch. Damien Robissout, Lilian Bossuet, Amaury Habrard
2024	J	`jnl`	Scoring the predictions: a way to improve profiling side-channel attacks. J. Cryptogr. Eng. Damien Robissout, Lilian Bossuet, Amaury Habrard
2023	J	`jnl`	Conditional Variational AutoEncoder based on Stochastic Attacks. IACR Trans. Cryptogr. Hardw. Embed. Syst. Gabriel Zaid, Lilian Bossuet, Mathieu Carbone, Amaury Habrard, Alexandre Venelli
2023	—	`conf`	Is My Neural Net Driven by the MDL Principle? ECML/PKDD (2) Eduardo Brandao, Stefan Duffner, Rémi Emonet, Amaury Habrard, François Jacquenet, Marc Sebban
2023	—	`conf`	Predictive Modeling of Body Shape Changes in Individuals on Dietetic Treatment Using Recurrent Networks. UCAmI (2) Nahuel E. Garcia-D'Urso, Pablo Ramon Guevara, Jorge Azorín López, Marc Sebban, Amaury Habrard, Andrés Fuster Guilló
2023	A*	`conf`	Proposal-Contrastive Pretraining for Object Detection from Fewer Data. ICLR Quentin Bouniot, Romaric Audigier, Angélique Loesch, Amaury Habrard
2023	J	`jnl`	Proposal-Contrastive Pretraining for Object Detection from Fewer Data. CoRR Quentin Bouniot, Romaric Audigier, Angélique Loesch, Amaury Habrard
2023	J	`jnl`	Towards Few-Annotation Learning for Object Detection: Are Transformer-based Models More Efficient ? CoRR Quentin Bouniot, Angélique Loesch, Romaric Audigier, Amaury Habrard
2023	A	`conf`	Towards Few-Annotation Learning for Object Detection: Are Transformer-based Models More Efficient? WACV Quentin Bouniot, Angélique Loesch, Amaury Habrard, Romaric Audigier
2022	—	`conf`	A Simple Way to Learn Metrics Between Attributed Graphs. LoG Yacouba Kaloga, Pierre Borgnat, Amaury Habrard
2022	J	`jnl`	A simple way to learn metrics between attributed graphs. CoRR Yacouba Kaloga, Pierre Borgnat, Amaury Habrard
2022	J	`jnl`	Conditional Variational AutoEncoder based on Stochastic Attack. IACR Cryptol. ePrint Arch. Gabriel Zaid, Lilian Bossuet, Mathieu Carbone, Amaury Habrard, Alexandre Venelli
2022	—	`conf`	Improving Few-Shot Learning Through Multi-task Representation Learning Theory. ECCV (20) Quentin Bouniot, Ievgen Redko, Romaric Audigier, Angélique Loesch, Amaury Habrard
2022	J	`jnl`	Learning PDE to Model Self-Organization of Matter. Entropy Eduardo Brandao, Jean-Philippe Colombier, Stefan Duffner, Rémi Emonet, Florence Garrelie, Amaury Habrard, François Jacquenet, Anthony Nakhoul, Marc Sebban
2022	J	`jnl`	MetaAP: A meta-tree-based ranking algorithm optimizing the average precision from imbalanced data. Pattern Recognit. Lett. Rémi Viola, Léo Gautheron, Amaury Habrard, Marc Sebban
2021	J	`jnl`	A General Framework for the Derandomization of PAC-Bayesian Bounds. CoRR Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
2021	J	`jnl`	A Nearest Neighbor Algorithm for Imbalanced Classification. Int. J. Artif. Intell. Tools Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Sébastien Riou, Marc Sebban
2021	A*	`conf`	A PAC-Bayes Analysis of Adversarial Robustness. NeurIPS Paul Viallard, Guillaume Vidot, Amaury Habrard, Emilie Morvant
2021	J	`jnl`	A PAC-Bayes Analysis of Adversarial Robustness. CoRR Guillaume Vidot, Paul Viallard, Amaury Habrard, Emilie Morvant
2021	J	`jnl`	Efficiency through Diversity in Ensemble Models applied to Side-Channel Attacks - A Case Study on Public-Key Algorithms -. IACR Cryptol. ePrint Arch. Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
2021	J	`jnl`	Efficiency through Diversity in Ensemble Models applied to Side-Channel Attacks - A Case Study on Public-Key Algorithms -. IACR Trans. Cryptogr. Hardw. Embed. Syst. Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
2021	J	`jnl`	Improving Deep Learning Networks for Profiled Side-Channel Analysis Using Performance Improvement Techniques. IACR Cryptol. ePrint Arch. Damien Robissout, Lilian Bossuet, Amaury Habrard, Vincent Grosso
2021	J	`jnl`	Improving Deep Learning Networks for Profiled Side-channel Analysis Using Performance Improvement Techniques. ACM J. Emerg. Technol. Comput. Syst. Damien Robissout, Lilian Bossuet, Amaury Habrard, Vincent Grosso
2021	J	`jnl`	Iterative multilinear optimization for planar model fitting under geometric constraints. PeerJ Comput. Sci. Jorge Azorín López, Marc Sebban, Andrés Fuster Guilló, Marcelo Saval-Calvo, Amaury Habrard
2021	A*	`conf`	Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. NeurIPS Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj
2021	J	`jnl`	Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. CoRR Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj
2021	Misc	`conf`	Multiview Variational Graph Autoencoders for Canonical Correlation Analysis. ICASSP Yacouba Kaloga, Pierre Borgnat, Sundeep Prabhakar Chepuri, Patrice Abry, Amaury Habrard
2021	J	`jnl`	Ranking Loss: Maximizing the Success Rate in Deep Learning Side-Channel Analysis. IACR Trans. Cryptogr. Hardw. Embed. Syst. Gabriel Zaid, Lilian Bossuet, François Dassance, Amaury Habrard, Alexandre Venelli
2021	J	`jnl`	Self-Bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound. CoRR Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
2021	—	`conf`	Self-bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound. ECML/PKDD (2) Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
2021	J	`jnl`	Variational graph autoencoders for multiview canonical correlation analysis. Signal Process. Yacouba Kaloga, Pierre Borgnat, Sundeep Prabhakar Chepuri, Patrice Abry, Amaury Habrard
2020	J	`jnl`	A survey on domain adaptation theory. CoRR Ievgen Redko, Emilie Morvant, Amaury Habrard, Marc Sebban, Younès Bennani
2020	B	`conf`	Dual Sequential Variational Autoencoders for Fraud Detection. IDA Ayman Alazizi, Amaury Habrard, François Jacquenet, Liyun He-Guelton, Frédéric Oblé
2020	J	`jnl`	Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening. Algorithms Louis Béthune, Yacouba Kaloga, Pierre Borgnat, Aurélien Garivier, Amaury Habrard
2020	J	`jnl`	Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening. CoRR Louis Béthune, Yacouba Kaloga, Pierre Borgnat, Aurélien Garivier, Amaury Habrard
2020	—	`conf`	Landmark-Based Ensemble Learning with Random Fourier Features and Gradient Boosting. ECML/PKDD (3) Léo Gautheron, Pascal Germain, Amaury Habrard, Guillaume Metzler, Emilie Morvant, Marc Sebban, Valentina Zantedeschi
2020	A*	`conf`	Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data. IJCAI Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Marc Sebban
2020	J	`jnl`	Methodology for Efficient CNN Architectures in Profiling Attacks. IACR Trans. Cryptogr. Hardw. Embed. Syst. Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
2020	J	`jnl`	Metric Learning from Imbalanced Data with Generalization Guarantees. Pattern Recognit. Lett. Léo Gautheron, Amaury Habrard, Emilie Morvant, Marc Sebban
2020	J	`jnl`	Multiview Variational Graph Autoencoders for Canonical Correlation Analysis. CoRR Yacouba Kaloga, Pierre Borgnat, Sundeep Prabhakar Chepuri, Patrice Abry, Amaury Habrard
2020	—	`conf`	Online Performance Evaluation of Deep Learning Networks for Profiled Side-Channel Analysis. COSADE Damien Robissout, Gabriel Zaid, Brice Colombier, Lilian Bossuet, Amaury Habrard
2020	J	`jnl`	Online Performance Evaluation of Deep Learning Networks for Side-Channel Analysis. IACR Cryptol. ePrint Arch. Damien Robissout, Gabriel Zaid, Brice Colombier, Lilian Bossuet, Amaury Habrard
2020	J	`jnl`	PAC-Bayes and domain adaptation. Neurocomputing Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2020	J	`jnl`	Putting Theory to Work: From Learning Bounds to Meta-Learning Algorithms. CoRR Quentin Bouniot, Ievgen Redko, Romaric Audigier, Angélique Loesch, Amaury Habrard
2020	J	`jnl`	Ranking Loss: Maximizing the Success Rate in Deep Learning Side-Channel Analysis. IACR Cryptol. ePrint Arch. Gabriel Zaid, Lilian Bossuet, François Dassance, Amaury Habrard, Alexandre Venelli
2020	J	`jnl`	Understanding Methodology for Efficient CNN Architectures in Profiling Attacks. IACR Cryptol. ePrint Arch. Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
2019	B	`conf`	An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data. ICTAI Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Sébastien Riou, Marc Sebban
2019	J	`jnl`	An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data. CoRR Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Sébastien Riou, Marc Sebban
2019	B	`conf`	Anomaly Detection, Consider Your Dataset First An Illustration on Fraud Detection. ICTAI Ayman Alazizi, Amaury Habrard, François Jacquenet, Liyun He-Guelton, Frédéric Oblé, Wissam Siblini
2019	J	`jnl`	Deep multi-Wasserstein unsupervised domain adaptation. Pattern Recognit. Lett. Tien-Nam Le, Amaury Habrard, Marc Sebban
2019	A*	`conf`	Differentially Private Optimal Transport: Application to Domain Adaptation. IJCAI Nam Lê Tien, Amaury Habrard, Marc Sebban
2019	A	`conf`	From Cost-Sensitive to Tight F-measure Bounds. AISTATS Kevin Bascol, Rémi Emonet, Élisa Fromont, Amaury Habrard, Guillaume Metzler, Marc Sebban
2019	J	`jnl`	Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting. CoRR Léo Gautheron, Pascal Germain, Amaury Habrard, Emilie Morvant, Marc Sebban, Valentina Zantedeschi
2019	J	`jnl`	Methodology for Efficient CNN Architectures in Profiling Attacks. IACR Cryptol. ePrint Arch. Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
2019	B	`conf`	Metric Learning from Imbalanced Data. ICTAI Léo Gautheron, Amaury Habrard, Emilie Morvant, Marc Sebban
2019	J	`jnl`	Metric Learning from Imbalanced Data. CoRR Léo Gautheron, Emilie Morvant, Amaury Habrard, Marc Sebban
2019	A*	`conf`	Near-Lossless Binarization of Word Embeddings. AAAI Julien Tissier, Christophe Gravier, Amaury Habrard
2019	J	`jnl`	On the analysis of adaptability in multi-source domain adaptation. Mach. Learn. Ievgen Redko, Amaury Habrard, Marc Sebban
2018	J	`jnl`	Learning maximum excluding ellipsoids from imbalanced data with theoretical guarantees. Pattern Recognit. Lett. Guillaume Metzler, Xavier Badiche, Brahim Belkasmi, Élisa Fromont, Amaury Habrard, Marc Sebban
2018	J	`jnl`	Near-lossless Binarization of Word Embeddings. CoRR Julien Tissier, Amaury Habrard, Christophe Gravier
2018	—	`conf`	Non-Linear Gradient Boosting for Class-Imbalance Learning. LIDTA@ECML/PKDD Jordan Fréry, Amaury Habrard, Marc Sebban, Liyun He-Guelton
2018	B	`conf`	Online Non-linear Gradient Boosting in Multi-latent Spaces. IDA Jordan Fréry, Amaury Habrard, Marc Sebban, Olivier Caelen, Liyun He-Guelton
2018	B	`conf`	Tree-Based Cost Sensitive Methods for Fraud Detection in Imbalanced Data. IDA Guillaume Metzler, Xavier Badiche, Brahim Belkasmi, Élisa Fromont, Amaury Habrard, Marc Sebban
2017	A*	`conf`	Dict2vec : Learning Word Embeddings using Lexical Dictionaries. EMNLP Julien Tissier, Christophe Gravier, Amaury Habrard
2017	—	`conf`	Efficient Top Rank Optimization with Gradient Boosting for Supervised Anomaly Detection. ECML/PKDD (1) Jordan Fréry, Amaury Habrard, Marc Sebban, Olivier Caelen, Liyun He-Guelton
2017	J	`jnl`	Joint Distribution Optimal Transportation for Domain Adaptation. CoRR Nicolas Courty, Rémi Flamary, Amaury Habrard, Alain Rakotomamonjy
2017	—	`conf`	Joint distribution optimal transportation for domain adaptation. NIPS Nicolas Courty, Rémi Flamary, Amaury Habrard, Alain Rakotomamonjy
2017	—	`conf`	Theoretical Analysis of Domain Adaptation with Optimal Transport. ECML/PKDD (2) Ievgen Redko, Amaury Habrard, Marc Sebban
2017	—	`ch.`	Unsupervised Domain Adaptation Based on Subspace Alignment. Domain Adaptation in Computer Vision Applications Basura Fernando, Rahaf Aljundi, Rémi Emonet, Amaury Habrard, Marc Sebban, Tinne Tuytelaars
2016	A*	`conf`	A New PAC-Bayesian Perspective on Domain Adaptation. ICML Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2016	J	`jnl`	A new boosting algorithm for provably accurate unsupervised domain adaptation. Knowl. Inf. Syst. Amaury Habrard, Jean-Philippe Peyrache, Marc Sebban
2016	J	`jnl`	Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning. J. Mach. Learn. Res. François Denis, Mattias Gybels, Amaury Habrard
2016	J	`jnl`	Learning discriminative tree edit similarities for linear classification - Application to melody recognition. Neurocomputing Aurélien Bellet, José Francisco Bernabeu, Amaury Habrard, Marc Sebban
2016	—	`conf`	Mapping Estimation for Discrete Optimal Transport. NIPS Michaël Perrot, Nicolas Courty, Rémi Flamary, Amaury Habrard
2016	J	`jnl`	Similarity Learning for Time Series Classification. CoRR Maria-Irina Nicolae, Éric Gaussier, Amaury Habrard, Marc Sebban
2016	J	`jnl`	Theoretical Analysis of Domain Adaptation with Optimal Transport. CoRR Ievgen Redko, Amaury Habrard, Marc Sebban
2015	J	`jnl`	A New PAC-Bayesian Perspective on Domain Adaptation. CoRR Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2015	A*	`conf`	A Theoretical Analysis of Metric Hypothesis Transfer Learning. ICML Michaël Perrot, Amaury Habrard
2015	—	`conf`	Algorithmic Robustness for Semi-Supervised (ε, γ, τ) -Good Metric Learning. ICONIP (1) Maria-Irina Nicolae, Marc Sebban, Amaury Habrard, Éric Gaussier, Massih-Reza Amini
2015	—	`conf`	Algorithmic Robustness for Semi-Supervised (ε, γ, τ)-Good Metric Learning. ICLR (Workshop) Maria-Irina Nicolae, Marc Sebban, Amaury Habrard, Éric Gaussier, Massih-Reza Amini
2015	J	`jnl`	An Improvement to the Domain Adaptation Bound in a PAC-Bayesian context. CoRR Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2015	—	`conf`	Joint Semi-supervised Similarity Learning for Linear Classification. ECML/PKDD (1) Maria-Irina Nicolae, Éric Gaussier, Amaury Habrard, Marc Sebban
2015	—	`book`	Metric Learning Aurélien Bellet, Amaury Habrard, Marc Sebban
2015	J	`jnl`	PAC-Bayesian Theorems for Domain Adaptation with Specialization to Linear Classifiers. CoRR Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2015	—	`conf`	Regressive Virtual Metric Learning. NIPS Michaël Perrot, Amaury Habrard
2015	J	`jnl`	Robustness and generalization for metric learning. Neurocomputing Aurélien Bellet, Amaury Habrard
2014	A*	`conf`	Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning. ICML François Denis, Mattias Gybels, Amaury Habrard
2014	J	`jnl`	Learning a priori constrained weighted majority votes. Mach. Learn. Aurélien Bellet, Amaury Habrard, Emilie Morvant, Marc Sebban
2014	—	`conf`	Majority Vote of Diverse Classifiers for Late Fusion. S+SSPR Emilie Morvant, Amaury Habrard, Stéphane Ayache
2014	J	`jnl`	Majority Vote of Diverse Classifiers for Late Fusion. CoRR Emilie Morvant, Amaury Habrard, Stéphane Ayache
2014	—	`conf`	Modeling Perceptual Color Differences by Local Metric Learning. ECCV (5) Michaël Perrot, Amaury Habrard, Damien Muselet, Marc Sebban
2014	—	`conf`	Some improvements of the spectral learning approach for probabilistic grammatical inference. ICGI Mattias Gybels, François Denis, Amaury Habrard
2014	J	`jnl`	Subspace Alignment For Domain Adaptation. CoRR Basura Fernando, Amaury Habrard, Marc Sebban, Tinne Tuytelaars
2013	—	`conf`	A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers. ICML (3) Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2013	J	`jnl`	A Survey on Metric Learning for Feature Vectors and Structured Data. CoRR Aurélien Bellet, Amaury Habrard, Marc Sebban
2013	—	`conf`	Boosting for Unsupervised Domain Adaptation. ECML/PKDD (2) Amaury Habrard, Jean-Philippe Peyrache, Marc Sebban
2013	J	`jnl`	Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning. CoRR François Denis, Mattias Gybels, Amaury Habrard
2013	J	`jnl`	Iterative Self-Labeling Domain Adaptation for Linear Structured Image Classification. Int. J. Artif. Intell. Tools Amaury Habrard, Jean-Philippe Peyrache, Marc Sebban
2013	A*	`conf`	Unsupervised Visual Domain Adaptation Using Subspace Alignment. ICCV Basura Fernando, Amaury Habrard, Marc Sebban, Tinne Tuytelaars
2012	J	`jnl`	Good edit similarity learning by loss minimization. Mach. Learn. Aurélien Bellet, Amaury Habrard, Marc Sebban
2012	J	`jnl`	PAC-Bayesian Learning and Domain Adaptation CoRR Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
2012	J	`jnl`	PAC-Bayesian Majority Vote for Late Classifier Fusion CoRR Emilie Morvant, Amaury Habrard, Stéphane Ayache
2012	J	`jnl`	Parsimonious unsupervised and semi-supervised domain adaptation with good similarity functions. Knowl. Inf. Syst. Emilie Morvant, Amaury Habrard, Stéphane Ayache
2012	J	`jnl`	Robustness and Generalization for Metric Learning CoRR Aurélien Bellet, Amaury Habrard
2012	A*	`conf`	Similarity Learning for Provably Accurate Sparse Linear Classification. ICML Aurélien Bellet, Amaury Habrard, Marc Sebban
2012	—	`conf`	Speeding Up Syntactic Learning Using Contextual Information. ICGI Leonor Becerra-Bonache, Élisa Fromont, Amaury Habrard, Michaël Perrot, Marc Sebban
2011	B	`conf`	An Experimental Study on Learning with Good Edit Similarity Functions. ICTAI Aurélien Bellet, Marc Sebban, Amaury Habrard
2011	B	`conf`	Domain Adaptation with Good Edit Similarities: A Sparse Way to Deal with Scaling and Rotation Problems in Image Classification. ICTAI Amaury Habrard, Jean-Philippe Peyrache, Marc Sebban
2011	—	`conf`	Learning Good Edit Similarities with Generalization Guarantees. ECML/PKDD (1) Aurélien Bellet, Amaury Habrard, Marc Sebban
2011	—	`conf`	On the Usefulness of Similarity Based Projection Spaces for Transfer Learning. SIMBAD Emilie Morvant, Amaury Habrard, Stéphane Ayache
2011	A*	`conf`	Sparse Domain Adaptation in Projection Spaces Based on Good Similarity Functions. ICDM Emilie Morvant, Amaury Habrard, Stéphane Ayache
2011	—	`conf`	VideoSense at TRECVID 2011: Semantic Indexing from Light Similarity Functions-based Domain Adaptation with Stacking. TRECVID Emilie Morvant, Stéphane Ayache, Amaury Habrard, Miriam Redi, Claudiu Tanase, Bernard Mérialdo, Bahjat Safadi, Franck Thollard, Nadia Derbas, Georges Quénot
2010	B	`conf`	A Spectral Approach for Probabilistic Grammatical Inference on Trees. ALT Raphaël Bailly, Amaury Habrard, François Denis
2010	J	`jnl`	Using Contextual Representations to Efficiently Learn Context-Free Languages. J. Mach. Learn. Res. Alexander Clark, Rémi Eyraud, Amaury Habrard
2009	B	`conf`	Learning Constrained Edit State Machines. ICTAI Laurent Boyer, Olivier Gandrillon, Amaury Habrard, Mathilde Pellerin, Marc Sebban
2008	—	`conf`	A Polynomial Algorithm for the Inference of Context Free Languages. ICGI Alexander Clark, Rémi Eyraud, Amaury Habrard
2008	J	`jnl`	Learning probabilistic models of tree edit distance. Pattern Recognit. Marc Bernard, Laurent Boyer, Amaury Habrard, Marc Sebban
2008	—	`conf`	Melody Recognition with Learned Edit Distances. SSPR/SPR Amaury Habrard, José Manuel Iñesta Quereda, David Rizo, Marc Sebban
2008	J	`jnl`	On Probability Distributions for Trees: Representations, Inference and Learning CoRR François Denis, Amaury Habrard, Rémi Gilleron, Marc Tommasi, Édouard Gilbert
2008	—	`conf`	Relevant Representations for the Inference of Rational Stochastic Tree Languages. ICGI François Denis, Édouard Gilbert, Amaury Habrard, Faissal Ouardi, Marc Tommasi
2008	—	`conf`	SEDiL: Software for Edit Distance Learning. ECML/PKDD (2) Laurent Boyer, Yann Esposito, Amaury Habrard, José Oncina, Marc Sebban
2007	—	`conf`	Learning Metrics Between Tree Structured Data: Application to Image Recognition. ECML Laurent Boyer, Amaury Habrard, Marc Sebban
2007	B	`conf`	Learning Rational Stochastic Tree Languages. ALT François Denis, Amaury Habrard
2006	—	`conf`	Learning Multiplicity Tree Automata. ICGI Amaury Habrard, José Oncina
2006	A*	`conf`	Learning Rational Stochastic Languages. COLT François Denis, Yann Esposito, Amaury Habrard
2006	—	`conf`	Learning Stochastic Tree Edit Distance. ECML Marc Bernard, Amaury Habrard, Marc Sebban
2006	J	`jnl`	Learning rational stochastic languages CoRR François Denis, Yann Esposito, Amaury Habrard
2006	J	`jnl`	Using Pseudo-Stochastic Rational Languages in Probabilistic Grammatical Inference CoRR Amaury Habrard, François Denis, Yann Esposito
2006	—	`conf`	Using Pseudo-stochastic Rational Languages in Probabilistic Grammatical Inference. ICGI Amaury Habrard, François Denis, Yann Esposito
2005	Misc	`conf`	Correction of Uniformly Noisy Distributions to Improve Probabilistic Grammatical Inference Algorithms. FLAIRS Amaury Habrard, Marc Bernard, Marc Sebban
2005	J	`jnl`	Detecting Irrelevant Subtrees to Improve Probabilistic Learning from Tree-structured Data. Fundam. Informaticae Amaury Habrard, Marc Bernard, Marc Sebban
2003	—	`conf`	Improvement of the State Merging Rule on Noisy Data in Probabilistic Grammatical Inference. ECML Amaury Habrard, Marc Bernard, Marc Sebban
2003	B	`conf`	Multi-relational Data Mining in Medical Databases. AIME Amaury Habrard, Marc Bernard, François Jacquenet
2002	—	`conf`	Generalized Stochastic Tree Automata for Multi-relational Data Mining. ICGI Amaury Habrard, Marc Bernard, François Jacquenet