Amaury Habrard

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 78

Top Venues

CoRR

IACR Cryptol. ePrint Arch.

IACR Trans. Cryptogr. Hardw. Embed. Syst.

Pattern Recognit. Lett.

Publications

Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
A general framework for the practical disintegration of PAC-Bayesian bounds. Mach. Learn. 113 (2) (2024)
Volodimir Mitarchuk, Clara Lacroce, Rémi Eyraud, Rémi Emonet, Amaury Habrard, Guillaume Rabusseau
Length independent PAC-Bayes bounds for Simple RNNs. AISTATS (2024)
Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. AISTATS (2024)
Damien Robissout, Lilian Bossuet, Amaury Habrard
Scoring the predictions: a way to improve profiling side-channel attacks. IACR Cryptol. ePrint Arch. 2024 (2024)
Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. CoRR (2024)
Quentin Bouniot, Angélique Loesch, Amaury Habrard, Romaric Audigier
Towards Few-Annotation Learning for Object Detection: Are Transformer-based Models More Efficient? WACV (2023)
Quentin Bouniot, Angélique Loesch, Romaric Audigier, Amaury Habrard
Towards Few-Annotation Learning for Object Detection: Are Transformer-based Models More Efficient ? CoRR (2023)
Quentin Bouniot, Romaric Audigier, Angélique Loesch, Amaury Habrard
Proposal-Contrastive Pretraining for Object Detection from Fewer Data. CoRR (2023)
Eduardo Brandao, Stefan Duffner, Rémi Emonet, Amaury Habrard, François Jacquenet, Marc Sebban
Is My Neural Net Driven by the MDL Principle? ECML/PKDD (2) (2023)
Gabriel Zaid, Lilian Bossuet, Mathieu Carbone, Amaury Habrard, Alexandre Venelli
Conditional Variational AutoEncoder based on Stochastic Attacks. IACR Trans. Cryptogr. Hardw. Embed. Syst. 2023 (2) (2023)
Quentin Bouniot, Romaric Audigier, Angélique Loesch, Amaury Habrard
Proposal-Contrastive Pretraining for Object Detection from Fewer Data. ICLR (2023)
Nahuel E. Garcia-D'Urso, Pablo Ramon Guevara, Jorge Azorín López, Marc Sebban, Amaury Habrard, Andrés Fuster Guilló
Predictive Modeling of Body Shape Changes in Individuals on Dietetic Treatment Using Recurrent Networks. UCAmI (2) (2023)
Yacouba Kaloga, Pierre Borgnat, Amaury Habrard
A Simple Way to Learn Metrics Between Attributed Graphs. LoG (2022)
Yacouba Kaloga, Pierre Borgnat, Amaury Habrard
A simple way to learn metrics between attributed graphs. CoRR (2022)
Quentin Bouniot, Ievgen Redko, Romaric Audigier, Angélique Loesch, Amaury Habrard
Improving Few-Shot Learning Through Multi-task Representation Learning Theory. ECCV (20) (2022)
Rémi Viola, Léo Gautheron, Amaury Habrard, Marc Sebban
MetaAP: A meta-tree-based ranking algorithm optimizing the average precision from imbalanced data. Pattern Recognit. Lett. 161 (2022)
Gabriel Zaid, Lilian Bossuet, Mathieu Carbone, Amaury Habrard, Alexandre Venelli
Conditional Variational AutoEncoder based on Stochastic Attack. IACR Cryptol. ePrint Arch. 2022 (2022)
Eduardo Brandao, Jean-Philippe Colombier, Stefan Duffner, Rémi Emonet, Florence Garrelie, Amaury Habrard, François Jacquenet, Anthony Nakhoul, Marc Sebban
Learning PDE to Model Self-Organization of Matter. Entropy 24 (8) (2022)
Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Sébastien Riou, Marc Sebban
A Nearest Neighbor Algorithm for Imbalanced Classification. Int. J. Artif. Intell. Tools 30 (3) (2021)
Jorge Azorín López, Marc Sebban, Andrés Fuster Guilló, Marcelo Saval-Calvo, Amaury Habrard
Iterative multilinear optimization for planar model fitting under geometric constraints. PeerJ Comput. Sci. 7 (2021)
Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. NeurIPS (2021)
Guillaume Vidot, Paul Viallard, Amaury Habrard, Emilie Morvant
A PAC-Bayes Analysis of Adversarial Robustness. CoRR (2021)
Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
Self-bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound. ECML/PKDD (2) (2021)
Paul Viallard, Guillaume Vidot, Amaury Habrard, Emilie Morvant
A PAC-Bayes Analysis of Adversarial Robustness. NeurIPS (2021)
Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
Efficiency through Diversity in Ensemble Models applied to Side-Channel Attacks - A Case Study on Public-Key Algorithms -. IACR Trans. Cryptogr. Hardw. Embed. Syst. 2021 (3) (2021)
Yacouba Kaloga, Pierre Borgnat, Sundeep Prabhakar Chepuri, Patrice Abry, Amaury Habrard
Multiview Variational Graph Autoencoders for Canonical Correlation Analysis. ICASSP (2021)
Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. CoRR (2021)
Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
A General Framework for the Derandomization of PAC-Bayesian Bounds. CoRR (2021)
Damien Robissout, Lilian Bossuet, Amaury Habrard, Vincent Grosso
Improving Deep Learning Networks for Profiled Side-channel Analysis Using Performance Improvement Techniques. ACM J. Emerg. Technol. Comput. Syst. 17 (3) (2021)
Damien Robissout, Lilian Bossuet, Amaury Habrard, Vincent Grosso
Improving Deep Learning Networks for Profiled Side-Channel Analysis Using Performance Improvement Techniques. IACR Cryptol. ePrint Arch. 2021 (2021)
Gabriel Zaid, Lilian Bossuet, François Dassance, Amaury Habrard, Alexandre Venelli
Ranking Loss: Maximizing the Success Rate in Deep Learning Side-Channel Analysis. IACR Trans. Cryptogr. Hardw. Embed. Syst. 2021 (1) (2021)
Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
Efficiency through Diversity in Ensemble Models applied to Side-Channel Attacks - A Case Study on Public-Key Algorithms -. IACR Cryptol. ePrint Arch. 2021 (2021)
Yacouba Kaloga, Pierre Borgnat, Sundeep Prabhakar Chepuri, Patrice Abry, Amaury Habrard
Variational graph autoencoders for multiview canonical correlation analysis. Signal Process. 188 (2021)
Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
Self-Bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound. CoRR (2021)
Léo Gautheron, Amaury Habrard, Emilie Morvant, Marc Sebban
Metric Learning from Imbalanced Data with Generalization Guarantees. Pattern Recognit. Lett. 133 (2020)
Ievgen Redko, Emilie Morvant, Amaury Habrard, Marc Sebban, Younès Bennani
A survey on domain adaptation theory. CoRR (2020)
Louis Béthune, Yacouba Kaloga, Pierre Borgnat, Aurélien Garivier, Amaury Habrard
Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening. CoRR (2020)
Damien Robissout, Gabriel Zaid, Brice Colombier, Lilian Bossuet, Amaury Habrard
Online Performance Evaluation of Deep Learning Networks for Side-Channel Analysis. IACR Cryptol. ePrint Arch. 2020 (2020)
Ayman Alazizi, Amaury Habrard, François Jacquenet, Liyun He-Guelton, Frédéric Oblé
Dual Sequential Variational Autoencoders for Fraud Detection. IDA (2020)
Yacouba Kaloga, Pierre Borgnat, Sundeep Prabhakar Chepuri, Patrice Abry, Amaury Habrard
Multiview Variational Graph Autoencoders for Canonical Correlation Analysis. CoRR (2020)
Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Marc Sebban
Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data. IJCAI (2020)
Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
Understanding Methodology for Efficient CNN Architectures in Profiling Attacks. IACR Cryptol. ePrint Arch. 2020 (2020)
Léo Gautheron, Pascal Germain, Amaury Habrard, Guillaume Metzler, Emilie Morvant, Marc Sebban, Valentina Zantedeschi
Landmark-Based Ensemble Learning with Random Fourier Features and Gradient Boosting. ECML/PKDD (3) (2020)
Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
Methodology for Efficient CNN Architectures in Profiling Attacks. IACR Trans. Cryptogr. Hardw. Embed. Syst. 2020 (1) (2020)
Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
PAC-Bayes and domain adaptation. Neurocomputing 379 (2020)
Louis Béthune, Yacouba Kaloga, Pierre Borgnat, Aurélien Garivier, Amaury Habrard
Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening. Algorithms 13 (9) (2020)
Damien Robissout, Gabriel Zaid, Brice Colombier, Lilian Bossuet, Amaury Habrard
Online Performance Evaluation of Deep Learning Networks for Profiled Side-Channel Analysis. COSADE (2020)
Quentin Bouniot, Ievgen Redko, Romaric Audigier, Angélique Loesch, Amaury Habrard
Putting Theory to Work: From Learning Bounds to Meta-Learning Algorithms. CoRR (2020)
Gabriel Zaid, Lilian Bossuet, François Dassance, Amaury Habrard, Alexandre Venelli
Ranking Loss: Maximizing the Success Rate in Deep Learning Side-Channel Analysis. IACR Cryptol. ePrint Arch. 2020 (2020)
Ievgen Redko, Amaury Habrard, Marc Sebban
On the analysis of adaptability in multi-source domain adaptation. Mach. Learn. 108 (8-9) (2019)
Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Sébastien Riou, Marc Sebban
An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data. CoRR (2019)
Ayman Alazizi, Amaury Habrard, François Jacquenet, Liyun He-Guelton, Frédéric Oblé, Wissam Siblini
Anomaly Detection, Consider Your Dataset First An Illustration on Fraud Detection. ICTAI (2019)
Gabriel Zaid, Lilian Bossuet, Amaury Habrard, Alexandre Venelli
Methodology for Efficient CNN Architectures in Profiling Attacks. IACR Cryptol. ePrint Arch. 2019 (2019)
Tien-Nam Le, Amaury Habrard, Marc Sebban
Deep multi-Wasserstein unsupervised domain adaptation. Pattern Recognit. Lett. 125 (2019)
Kevin Bascol, Rémi Emonet, Élisa Fromont, Amaury Habrard, Guillaume Metzler, Marc Sebban
From Cost-Sensitive to Tight F-measure Bounds. AISTATS (2019)
Julien Tissier, Christophe Gravier, Amaury Habrard
Near-Lossless Binarization of Word Embeddings. AAAI (2019)
Léo Gautheron, Amaury Habrard, Emilie Morvant, Marc Sebban
Metric Learning from Imbalanced Data. ICTAI (2019)
Nam Lê Tien, Amaury Habrard, Marc Sebban
Differentially Private Optimal Transport: Application to Domain Adaptation. IJCAI (2019)
Léo Gautheron, Pascal Germain, Amaury Habrard, Emilie Morvant, Marc Sebban, Valentina Zantedeschi
Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting. CoRR (2019)
Rémi Viola, Rémi Emonet, Amaury Habrard, Guillaume Metzler, Sébastien Riou, Marc Sebban
An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data. ICTAI (2019)
Léo Gautheron, Emilie Morvant, Amaury Habrard, Marc Sebban
Metric Learning from Imbalanced Data. CoRR (2019)
Jordan Fréry, Amaury Habrard, Marc Sebban, Liyun He-Guelton
Non-Linear Gradient Boosting for Class-Imbalance Learning. LIDTA@ECML/PKDD (2018)
Julien Tissier, Amaury Habrard, Christophe Gravier
Near-lossless Binarization of Word Embeddings. CoRR (2018)
Guillaume Metzler, Xavier Badiche, Brahim Belkasmi, Élisa Fromont, Amaury Habrard, Marc Sebban
Learning maximum excluding ellipsoids from imbalanced data with theoretical guarantees. Pattern Recognit. Lett. 112 (2018)
Guillaume Metzler, Xavier Badiche, Brahim Belkasmi, Élisa Fromont, Amaury Habrard, Marc Sebban
Tree-Based Cost Sensitive Methods for Fraud Detection in Imbalanced Data. IDA (2018)
Jordan Fréry, Amaury Habrard, Marc Sebban, Olivier Caelen, Liyun He-Guelton
Online Non-linear Gradient Boosting in Multi-latent Spaces. IDA (2018)
Jordan Fréry, Amaury Habrard, Marc Sebban, Olivier Caelen, Liyun He-Guelton
Efficient Top Rank Optimization with Gradient Boosting for Supervised Anomaly Detection. ECML/PKDD (1) (2017)
Julien Tissier, Christophe Gravier, Amaury Habrard
Dict2vec : Learning Word Embeddings using Lexical Dictionaries. EMNLP (2017)
Nicolas Courty, Rémi Flamary, Amaury Habrard, Alain Rakotomamonjy
Joint Distribution Optimal Transportation for Domain Adaptation. CoRR (2017)
Ievgen Redko, Amaury Habrard, Marc Sebban
Theoretical Analysis of Domain Adaptation with Optimal Transport. ECML/PKDD (2) (2017)
Nicolas Courty, Rémi Flamary, Amaury Habrard, Alain Rakotomamonjy
Joint distribution optimal transportation for domain adaptation. NIPS (2017)
Ievgen Redko, Amaury Habrard, Marc Sebban
Theoretical Analysis of Domain Adaptation with Optimal Transport. CoRR (2016)
Amaury Habrard, Jean-Philippe Peyrache, Marc Sebban
A new boosting algorithm for provably accurate unsupervised domain adaptation. Knowl. Inf. Syst. 47 (1) (2016)
Michaël Perrot, Nicolas Courty, Rémi Flamary, Amaury Habrard
Mapping Estimation for Discrete Optimal Transport. NIPS (2016)
Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
A New PAC-Bayesian Perspective on Domain Adaptation. ICML (2016)
Aurélien Bellet, José Francisco Bernabeu, Amaury Habrard, Marc Sebban
Learning discriminative tree edit similarities for linear classification - Application to melody recognition. Neurocomputing 214 (2016)
François Denis, Mattias Gybels, Amaury Habrard
Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning. J. Mach. Learn. Res. 17 (2016)
Maria-Irina Nicolae, Éric Gaussier, Amaury Habrard, Marc Sebban
Similarity Learning for Time Series Classification. CoRR (2016)
Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
A New PAC-Bayesian Perspective on Domain Adaptation. CoRR (2015)
Maria-Irina Nicolae, Marc Sebban, Amaury Habrard, Éric Gaussier, Massih-Reza Amini
Algorithmic Robustness for Semi-Supervised (ε, γ, τ) -Good Metric Learning. ICONIP (1) (2015)
Aurélien Bellet, Amaury Habrard
Robustness and generalization for metric learning. Neurocomputing 151 (2015)
Michaël Perrot, Amaury Habrard
A Theoretical Analysis of Metric Hypothesis Transfer Learning. ICML (2015)
Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
PAC-Bayesian Theorems for Domain Adaptation with Specialization to Linear Classifiers. CoRR (2015)
Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
An Improvement to the Domain Adaptation Bound in a PAC-Bayesian context. CoRR (2015)
Maria-Irina Nicolae, Éric Gaussier, Amaury Habrard, Marc Sebban
Joint Semi-supervised Similarity Learning for Linear Classification. ECML/PKDD (1) (2015)
Michaël Perrot, Amaury Habrard
Regressive Virtual Metric Learning. NIPS (2015)
Maria-Irina Nicolae, Marc Sebban, Amaury Habrard, Éric Gaussier, Massih-Reza Amini
Algorithmic Robustness for Semi-Supervised (ε, γ, τ)-Good Metric Learning. ICLR (Workshop) (2015)
François Denis, Mattias Gybels, Amaury Habrard
Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning. ICML (2014)
Aurélien Bellet, Amaury Habrard, Emilie Morvant, Marc Sebban
Learning a priori constrained weighted majority votes. Mach. Learn. 97 (1-2) (2014)
Michaël Perrot, Amaury Habrard, Damien Muselet, Marc Sebban
Modeling Perceptual Color Differences by Local Metric Learning. ECCV (5) (2014)
Basura Fernando, Amaury Habrard, Marc Sebban, Tinne Tuytelaars
Subspace Alignment For Domain Adaptation. CoRR (2014)
Emilie Morvant, Amaury Habrard, Stéphane Ayache
Majority Vote of Diverse Classifiers for Late Fusion. S+SSPR (2014)
Mattias Gybels, François Denis, Amaury Habrard
Some improvements of the spectral learning approach for probabilistic grammatical inference. ICGI (2014)
Emilie Morvant, Amaury Habrard, Stéphane Ayache
Majority Vote of Diverse Classifiers for Late Fusion. CoRR (2014)
Pascal Germain, Amaury Habrard, François Laviolette, Emilie Morvant
A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers. ICML (3) (2013)
Amaury Habrard, Jean-Philippe Peyrache, Marc Sebban
Iterative Self-Labeling Domain Adaptation for Linear Structured Image Classification. Int. J. Artif. Intell. Tools 22 (5) (2013)
Amaury Habrard, Jean-Philippe Peyrache, Marc Sebban
Boosting for Unsupervised Domain Adaptation. ECML/PKDD (2) (2013)
Aurélien Bellet, Amaury Habrard, Marc Sebban
A Survey on Metric Learning for Feature Vectors and Structured Data. CoRR (2013)
Basura Fernando, Amaury Habrard, Marc Sebban, Tinne Tuytelaars
Unsupervised Visual Domain Adaptation Using Subspace Alignment. ICCV (2013)
François Denis, Mattias Gybels, Amaury Habrard
Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning. CoRR (2013)

Amaury Habrard.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Amaury Habrard