| 2025 | ICML | A Bregman Proximal Viewpoint on Neural Operators. | Abdel-Rahim Mezidi, Jordan Patracone, Saverio Salzo, Amaury Habrard, Massimiliano Pontil, Rmi Emonet, Marc Sebban |
| 2024 | AISTATS | Length independent PAC-Bayes bounds for Simple RNNs. | Volodimir Mitarchuk, Clara Lacroce, Rmi Eyraud, Rmi Emonet, Amaury Habrard, Guillaume Rabusseau |
| 2024 | AISTATS | Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. | Paul Viallard, Rmi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi |
| 2024 | IJCNN | Generative shape deformation with optimal transport using learned transformations. | Jorge Azorn Lpez, Marc Sebban, Nahuel E. Garcia-D'Urso, Amaury Habrard, Andrs Fuster Guill |
| 2024 | WiMob | Advanced Traffic Engineering in WAN Using Graph Attention Networks. | Sami Marouani, Kamal Singh, Baptiste Jeudy, Abbas Bradai, Amaury Habrard |
| 2023 | ICLR | Proposal-Contrastive Pretraining for Object Detection from Fewer Data. | Quentin Bouniot, Romaric Audigier, Anglique Loesch, Amaury Habrard |
| 2023 | WACV | Towards Few-Annotation Learning for Object Detection: Are Transformer-based Models More Efficient? | Quentin Bouniot, Anglique Loesch, Amaury Habrard, Romaric Audigier |
| 2022 | ECCV | Improving Few-Shot Learning Through Multi-task Representation Learning Theory. | Quentin Bouniot, Ievgen Redko, Romaric Audigier, Anglique Loesch, Amaury Habrard |
| 2021 | ICASSP | Multiview Variational Graph Autoencoders for Canonical Correlation Analysis. | Yacouba Kaloga, Pierre Borgnat, Sundeep Prabhakar Chepuri, Patrice Abry, Amaury Habrard |
| 2020 | IJCAI | Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data. | Rmi Viola, Rmi Emonet, Amaury Habrard, Guillaume Metzler, Marc Sebban |
| 2020 | IDA | Dual Sequential Variational Autoencoders for Fraud Detection. | Ayman Alazizi, Amaury Habrard, Franois Jacquenet, Liyun He-Guelton, Frdric Obl |
| 2019 | AAAI | Near-Lossless Binarization of Word Embeddings. | Julien Tissier, Christophe Gravier, Amaury Habrard |
| 2019 | AISTATS | From Cost-Sensitive to Tight F-measure Bounds. | Kevin Bascol, Rmi Emonet, lisa Fromont, Amaury Habrard, Guillaume Metzler, Marc Sebban |
| 2019 | IJCAI | Differentially Private Optimal Transport: Application to Domain Adaptation. | Nam L Tien, Amaury Habrard, Marc Sebban |
| 2019 | ICTAI | Anomaly Detection, Consider Your Dataset First An Illustration on Fraud Detection. | Ayman Alazizi, Amaury Habrard, Franois Jacquenet, Liyun He-Guelton, Frdric Obl, Wissam Siblini |
| 2019 | ICTAI | Metric Learning from Imbalanced Data. | Lo Gautheron, Amaury Habrard, Emilie Morvant, Marc Sebban |
| 2019 | ICTAI | An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data. | Rmi Viola, Rmi Emonet, Amaury Habrard, Guillaume Metzler, Sbastien Riou, Marc Sebban |
| 2018 | IDA | Online Non-linear Gradient Boosting in Multi-latent Spaces. | Jordan Frry, Amaury Habrard, Marc Sebban, Olivier Caelen, Liyun He-Guelton |
| 2018 | IDA | Tree-Based Cost Sensitive Methods for Fraud Detection in Imbalanced Data. | Guillaume Metzler, Xavier Badiche, Brahim Belkasmi, lisa Fromont, Amaury Habrard, Marc Sebban |
| 2017 | EMNLP | Dict2vec : Learning Word Embeddings using Lexical Dictionaries. | Julien Tissier, Christophe Gravier, Amaury Habrard |
| 2016 | ICML | A New PAC-Bayesian Perspective on Domain Adaptation. | Pascal Germain, Amaury Habrard, Franois Laviolette, Emilie Morvant |
| 2015 | ICML | A Theoretical Analysis of Metric Hypothesis Transfer Learning. | Michal Perrot, Amaury Habrard |
| 2015 | ICONIP | Algorithmic Robustness for Semi-Supervised (ε, γ, τ) -Good Metric Learning. | Maria-Irina Nicolae, Marc Sebban, Amaury Habrard, ric Gaussier, Massih-Reza Amini |
| 2014 | ECCV | Modeling Perceptual Color Differences by Local Metric Learning. | Michal Perrot, Amaury Habrard, Damien Muselet, Marc Sebban |
| 2014 | ICML | Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning. | Franois Denis, Mattias Gybels, Amaury Habrard |
| 2014 | SSPR | Majority Vote of Diverse Classifiers for Late Fusion. | Emilie Morvant, Amaury Habrard, Stphane Ayache |
| 2013 | ICCV | Unsupervised Visual Domain Adaptation Using Subspace Alignment. | Basura Fernando, Amaury Habrard, Marc Sebban, Tinne Tuytelaars |
| 2013 | ICML | A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers. | Pascal Germain, Amaury Habrard, Franois Laviolette, Emilie Morvant |
| 2012 | ICML | Similarity Learning for Provably Accurate Sparse Linear Classification. | Aurlien Bellet, Amaury Habrard, Marc Sebban |
| 2011 | ICDM | Sparse Domain Adaptation in Projection Spaces Based on Good Similarity Functions. | Emilie Morvant, Amaury Habrard, Stphane Ayache |
| 2011 | ICTAI | An Experimental Study on Learning with Good Edit Similarity Functions. | Aurlien Bellet, Marc Sebban, Amaury Habrard |
| 2011 | ICTAI | Domain Adaptation with Good Edit Similarities: A Sparse Way to Deal with Scaling and Rotation Problems in Image Classification. | Amaury Habrard, Jean-Philippe Peyrache, Marc Sebban |
| 2010 | ALT | A Spectral Approach for Probabilistic Grammatical Inference on Trees. | Raphal Bailly, Amaury Habrard, Franois Denis |
| 2009 | ICTAI | Learning Constrained Edit State Machines. | Laurent Boyer, Olivier Gandrillon, Amaury Habrard, Mathilde Pellerin, Marc Sebban |
| 2008 | SSPR | Melody Recognition with Learned Edit Distances. | Amaury Habrard, Jos Manuel Iesta Quereda, David Rizo, Marc Sebban |
| 2007 | ALT | Learning Rational Stochastic Tree Languages. | Franois Denis, Amaury Habrard |
| 2006 | COLT | Learning Rational Stochastic Languages. | Franois Denis, Yann Esposito, Amaury Habrard |
| 2005 | FlAIRS | Correction of Uniformly Noisy Distributions to Improve Probabilistic Grammatical Inference Algorithms. | Amaury Habrard, Marc Bernard, Marc Sebban |
| 2003 | AIME | Multi-relational Data Mining in Medical Databases. | Amaury Habrard, Marc Bernard, Franois Jacquenet |