Amaury Habrard

J. Cryptogr. Eng., September, 2024

A general framework for the practical disintegration of PAC-Bayesian bounds.

[BibT_eX]

[DOI]

Mach. Learn., February, 2024

Advanced Traffic Engineering in WAN Using Graph Attention Networks.

[BibT_eX]

[DOI]

Proceedings of the 20th International Conference on Wireless and Mobile Computing, 2024

A Theoretically Grounded Extension of Universal Attacks from the Attacker's Viewpoint.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Approximation Error of Sobolev Regular Functions with Tanh Neural Networks: Theoretical Impact on PINNs.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Generative shape deformation with optimal transport using learned transformations.

[BibT_eX]

[DOI]

Jorge Azorín López

Nahuel E. Garcia-D'Urso

Andrés Fuster Guilló

Proceedings of the International Joint Conference on Neural Networks, 2024

Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Length independent PAC-Bayes bounds for Simple RNNs.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Conditional Variational AutoEncoder based on Stochastic Attacks.

[BibT_eX]

[DOI]

IACR Trans. Cryptogr. Hardw. Embed. Syst., 2023

Towards Few-Annotation Learning for Object Detection: Are Transformer-based Models More Efficient?

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Predictive Modeling of Body Shape Changes in Individuals on Dietetic Treatment Using Recurrent Networks.

[BibT_eX]

[DOI]

Nahuel E. Garcia-D'Urso

Proceedings of the 15th International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2023), 2023

Is My Neural Net Driven by the MDL Principle?

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Proposal-Contrastive Pretraining for Object Detection from Fewer Data.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

MetaAP: A meta-tree-based ranking algorithm optimizing the average precision from imbalanced data.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2022

Conditional Variational AutoEncoder based on Stochastic Attack.

[BibT_eX]

[DOI]

IACR Cryptol. ePrint Arch., 2022

Learning PDE to Model Self-Organization of Matter.

[BibT_eX]

[DOI]

Eduardo Brandao

Jean-Philippe Colombier

Entropy, 2022

A Simple Way to Learn Metrics Between Attributed Graphs.

[BibT_eX]

[DOI]

Yacouba Kaloga

Pierre Borgnat

Sundeep Prabhakar Chepuri

Proceedings of the Learning on Graphs Conference, 2022

Improving Few-Shot Learning Through Multi-task Representation Learning Theory.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Efficiency through Diversity in Ensemble Models applied to Side-Channel Attacks - A Case Study on Public-Key Algorithms -.

[BibT_eX]

[DOI]

IACR Trans. Cryptogr. Hardw. Embed. Syst., 2021

Ranking Loss: Maximizing the Success Rate in Deep Learning Side-Channel Analysis.

[BibT_eX]

[DOI]

IACR Trans. Cryptogr. Hardw. Embed. Syst., 2021

Variational graph autoencoders for multiview canonical correlation analysis.

[BibT_eX]

[DOI]

Yacouba Kaloga

Pierre Borgnat

Patrice Abry

Signal Process., 2021

Iterative multilinear optimization for planar model fitting under geometric constraints.

[BibT_eX]

[DOI]

PeerJ Comput. Sci., 2021

Improving Deep Learning Networks for Profiled Side-channel Analysis Using Performance Improvement Techniques.

[BibT_eX]

[DOI]

ACM J. Emerg. Technol. Comput. Syst., 2021

A Nearest Neighbor Algorithm for Imbalanced Classification.

[BibT_eX]

[DOI]

Int. J. Artif. Intell. Tools, 2021

A General Framework for the Derandomization of PAC-Bayesian Bounds.

[BibT_eX]

[DOI]

CoRR, 2021

Self-bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound.

[BibT_eX]

[DOI]

Sundeep Prabhakar Chepuri

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A PAC-Bayes Analysis of Adversarial Robustness.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Multiview Variational Graph Autoencoders for Canonical Correlation Analysis.

[BibT_eX]

[DOI]

Yacouba Kaloga

Pierre Borgnat

Patrice Abry

Proceedings of the IEEE International Conference on Acoustics, 2021

2020

Methodology for Efficient CNN Architectures in Profiling Attacks.

[BibT_eX]

[DOI]

IACR Trans. Cryptogr. Hardw. Embed. Syst., 2020

Metric Learning from Imbalanced Data with Generalization Guarantees.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2020

PAC-Bayes and domain adaptation.

[BibT_eX]

[DOI]

Neurocomputing, 2020

Understanding Methodology for Efficient CNN Architectures in Profiling Attacks.

[BibT_eX]

[DOI]

IACR Cryptol. ePrint Arch., 2020

Online Performance Evaluation of Deep Learning Networks for Side-Channel Analysis.

[BibT_eX]

[DOI]

IACR Cryptol. ePrint Arch., 2020

Putting Theory to Work: From Learning Bounds to Meta-Learning Algorithms.

[BibT_eX]

[DOI]

CoRR, 2020

A survey on domain adaptation theory.

[BibT_eX]

[DOI]

CoRR, 2020

Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening.

[BibT_eX]

[DOI]

Algorithms, 2020

Landmark-Based Ensemble Learning with Random Fourier Features and Gradient Boosting.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Dual Sequential Variational Autoencoders for Fraud Detection.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

Online Performance Evaluation of Deep Learning Networks for Profiled Side-Channel Analysis.

[BibT_eX]

[DOI]

Proceedings of the Constructive Side-Channel Analysis and Secure Design, 2020

2019

Deep multi-Wasserstein unsupervised domain adaptation.

[BibT_eX]

[DOI]

Tien-Nam Le

Pattern Recognit. Lett., 2019

On the analysis of adaptability in multi-source domain adaptation.

[BibT_eX]

[DOI]

Ievgen Redko

Mach. Learn., 2019

Learning Landmark-Based Ensembles with Random Fourier Features and Gradient Boosting.

[BibT_eX]

[DOI]

CoRR, 2019

Differentially Private Optimal Transport: Application to Domain Adaptation.

[BibT_eX]

[DOI]

Nam Lê Tien

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

An Adjusted Nearest Neighbor Algorithm Maximizing the F-Measure from Imbalanced Data.

[BibT_eX]

[DOI]

Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019

Metric Learning from Imbalanced Data.

[BibT_eX]

[DOI]

Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019

Anomaly Detection, Consider Your Dataset First An Illustration on Fraud Detection.

[BibT_eX]

[DOI]

Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 2019

From Cost-Sensitive to Tight F-measure Bounds.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Near-Lossless Binarization of Word Embeddings.

[BibT_eX]

[DOI]

Julien Tissier

Christophe Gravier

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Learning maximum excluding ellipsoids from imbalanced data with theoretical guarantees.

[BibT_eX]

[DOI]

Pattern Recognit. Lett., 2018

Non-Linear Gradient Boosting for Class-Imbalance Learning.

[BibT_eX]

[DOI]

Proceedings of the Second International Workshop on Learning with Imbalanced Domains: Theory and Applications, 2018

Tree-Based Cost Sensitive Methods for Fraud Detection in Imbalanced Data.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis XVII, 2018

Online Non-linear Gradient Boosting in Multi-latent Spaces.

[BibT_eX]

[DOI]

Proceedings of the Advances in Intelligent Data Analysis XVII, 2018

2017

Unsupervised Domain Adaptation Based on Subspace Alignment.

[BibT_eX]

[DOI]

Proceedings of the Domain Adaptation in Computer Vision Applications., 2017

Theoretical Analysis of Domain Adaptation with Optimal Transport.

[BibT_eX]

[DOI]

Ievgen Redko

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Efficient Top Rank Optimization with Gradient Boosting for Supervised Anomaly Detection.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Joint distribution optimal transportation for domain adaptation.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Dict2vec : Learning Word Embeddings using Lexical Dictionaries.

[BibT_eX]

[DOI]

Julien Tissier

Christophe Gravier

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

2016

A new boosting algorithm for provably accurate unsupervised domain adaptation.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2016

Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning.

[BibT_eX]

[DOI]

Mattias Gybels

J. Mach. Learn. Res., 2016

Learning discriminative tree edit similarities for linear classification - Application to melody recognition.

[BibT_eX]

[DOI]

José Francisco Bernabeu

Neurocomputing, 2016

Similarity Learning for Time Series Classification.

[BibT_eX]

[DOI]

CoRR, 2016

Mapping Estimation for Discrete Optimal Transport.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

A New PAC-Bayesian Perspective on Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Metric Learning

[BibT_eX]

[DOI]

Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers, ISBN: 978-3-031-01572-4, 2015

Robustness and generalization for metric learning.

[BibT_eX]

[DOI]

Neurocomputing, 2015

Algorithmic Robustness for Semi-Supervised (ε, γ, τ)-Good Metric Learning.

[BibT_eX]

[DOI]

Proceedings of the 3rd International Conference on Learning Representations, 2015

PAC-Bayesian Theorems for Domain Adaptation with Specialization to Linear Classifiers.

[BibT_eX]

[DOI]

CoRR, 2015

An Improvement to the Domain Adaptation Bound in a PAC-Bayesian context.

[BibT_eX]

[DOI]

CoRR, 2015

Joint Semi-supervised Similarity Learning for Linear Classification.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

Regressive Virtual Metric Learning.

[BibT_eX]

[DOI]

Michaël Perrot

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

A Theoretical Analysis of Metric Hypothesis Transfer Learning.

[BibT_eX]

[DOI]

Michaël Perrot

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Learning a priori constrained weighted majority votes.

[BibT_eX]

[DOI]

Mach. Learn., 2014

Subspace Alignment For Domain Adaptation.

[BibT_eX]

[DOI]

CoRR, 2014

Majority Vote of Diverse Classifiers for Late Fusion.

[BibT_eX]

[DOI]

Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2014

Some improvements of the spectral learning approach for probabilistic grammatical inference.

[BibT_eX]

[DOI]

Mattias Gybels

Proceedings of the 12th International Conference on Grammatical Inference, 2014

Modeling Perceptual Color Differences by Local Metric Learning.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2014, 2014

2013

Iterative Self-Labeling Domain Adaptation for Linear Structured Image Classification.

[BibT_eX]

[DOI]

Int. J. Artif. Intell. Tools, 2013

A Survey on Metric Learning for Feature Vectors and Structured Data.

[BibT_eX]

[DOI]

CoRR, 2013

Boosting for Unsupervised Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers.

[BibT_eX]

[DOI]

Proceedings of the 30th International Conference on Machine Learning, 2013

Unsupervised Visual Domain Adaptation Using Subspace Alignment.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Computer Vision, 2013

2012

Good edit similarity learning by loss minimization.

[BibT_eX]

[DOI]

Mach. Learn., 2012

Parsimonious unsupervised and semi-supervised domain adaptation with good similarity functions.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2012

Speeding Up Syntactic Learning Using Contextual Information.

[BibT_eX]

[DOI]

Leonor Becerra-Bonache

Proceedings of the Eleventh International Conference on Grammatical Inference, 2012

PAC-Bayesian Learning and Domain Adaptation

[BibT_eX]

[DOI]

CoRR, 2012

PAC-Bayesian Majority Vote for Late Classifier Fusion

[BibT_eX]

[DOI]

CoRR, 2012

Similarity Learning for Provably Accurate Sparse Linear Classification.

[BibT_eX]

[DOI]

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

VideoSense at TRECVID 2011: Semantic Indexing from Light Similarity Functions-based Domain Adaptation with Stacking.

[BibT_eX]

[DOI]

Proceedings of the 2011 TREC Video Retrieval Evaluation, 2011

On the Usefulness of Similarity Based Projection Spaces for Transfer Learning.

[BibT_eX]

[DOI]

Proceedings of the Similarity-Based Pattern Recognition - First International Workshop, 2011

Learning Good Edit Similarities with Generalization Guarantees.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

Domain Adaptation with Good Edit Similarities: A Sparse Way to Deal with Scaling and Rotation Problems in Image Classification.

[BibT_eX]

[DOI]

Proceedings of the IEEE 23rd International Conference on Tools with Artificial Intelligence, 2011

An Experimental Study on Learning with Good Edit Similarity Functions.

[BibT_eX]

[DOI]

Proceedings of the IEEE 23rd International Conference on Tools with Artificial Intelligence, 2011

Sparse Domain Adaptation in Projection Spaces Based on Good Similarity Functions.

[BibT_eX]

[DOI]

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2010

Using Contextual Representations to Efficiently Learn Context-Free Languages.

[BibT_eX]

[DOI]

Alexander Clark

Rémi Eyraud

J. Mach. Learn. Res., 2010

A Spectral Approach for Probabilistic Grammatical Inference on Trees.

[BibT_eX]

[DOI]

Raphaël Bailly

Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010

2009

Learning Constrained Edit State Machines.

[BibT_eX]

[DOI]

Proceedings of the ICTAI 2009, 2009

2008

Learning probabilistic models of tree edit distance.

[BibT_eX]

[DOI]

Pattern Recognit., 2008

On Probability Distributions for Trees: Representations, Inference and Learning

[BibT_eX]

[DOI]

CoRR, 2008

Melody Recognition with Learned Edit Distances.

[BibT_eX]

[DOI]

José Manuel Iñesta Quereda

David Rizo

Proceedings of the Structural, 2008

SEDiL: Software for Edit Distance Learning.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008

Relevant Representations for the Inference of Rational Stochastic Tree Languages.

[BibT_eX]

[DOI]

Proceedings of the Grammatical Inference: Algorithms and Applications, 2008

A Polynomial Algorithm for the Inference of Context Free Languages.

[BibT_eX]

[DOI]

Alexander Clark

Rémi Eyraud

Proceedings of the Grammatical Inference: Algorithms and Applications, 2008

2007

Learning Metrics Between Tree Structured Data: Application to Image Recognition.

[BibT_eX]

[DOI]

Laurent Boyer

Proceedings of the Machine Learning: ECML 2007, 2007

Learning Rational Stochastic Tree Languages.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Learning Theory, 18th International Conference, 2007

2006

Learning Multiplicity Tree Automata.

[BibT_eX]

[DOI]

José Oncina

Proceedings of the Grammatical Inference: Algorithms and Applications, 2006

Using Pseudo-stochastic Rational Languages in Probabilistic Grammatical Inference.

[BibT_eX]

[DOI]

Yann Esposito

Proceedings of the Grammatical Inference: Algorithms and Applications, 2006

Learning Stochastic Tree Edit Distance.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning: ECML 2006, 2006

Learning Rational Stochastic Languages.

[BibT_eX]

[DOI]

Yann Esposito

Proceedings of the Learning Theory, 19th Annual Conference on Learning Theory, 2006

2005

Detecting Irrelevant Subtrees to Improve Probabilistic Learning from Tree-structured Data.

[BibT_eX]

[DOI]

Fundam. Informaticae, 2005

Correction of Uniformly Noisy Distributions to Improve Probabilistic Grammatical Inference Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Eighteenth International Florida Artificial Intelligence Research Society Conference, 2005

2003

Improvement of the State Merging Rule on Noisy Data in Probabilistic Grammatical Inference.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning: ECML 2003, 2003

Multi-relational Data Mining in Medical Databases.

[BibT_eX]

[DOI]

François Jacquenet

Proceedings of the Artificial Intelligence in Medicine, 2003

2002

Generalized Stochastic Tree Automata for Multi-relational Data Mining.

[BibT_eX]

[DOI]