← Authors

Amaury Habrard

23 papers · 2010–2025 · 11 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (11) πŸƒ Academic Marathon (15) 🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (6) πŸ—ΊοΈ Taxonomy Completionist (39) πŸ† Grand Slam πŸ—ƒοΈ Keyword Collector (86) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ’Ž Century Club (23) ❓ The Questioner πŸ”₯ Unstoppable (7)

Conferences

ICML (5) NIPS (5) AISTATS (3) IJCAI (2) JMLR (2) AAAI (1) ECCV (1) EMNLP (1) ICCV (1) ICLR (1) WACV (1)

Top co-authors

RΓ©mi Emonet (6) Emilie Morvant (5) Marc Sebban (5) Pascal Germain (3) Romaric Audigier (3) Quentin Bouniot (3) Paul Viallard (3) MichaΓ«l Perrot (3) AngΓ©lique Loesch (3) Valentina Zantedeschi (2)

Keywords

domain adaptation (6) optimal transport (4) generalization bound (4) transfer learning (4) majority vote (3) metric learning (3) weighted automaton (2) representation learning (2) few-shot learning (2) hankel matrix (2) pac-bayes bound (2) singular value decomposition (2) word embedding (2) text classification (2) pac-bayes theory (2) spectral learning (2) concentration bound (2) unsupervised learning (2) convex optimization (1) learning theory (1)

Papers

A Bregman Proximal Viewpoint on Neural Operators ICML 2025
Length independent PAC-Bayes bounds for Simple RNNs AISTATS 2024
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures AISTATS 2024
Proposal-Contrastive Pretraining for Object Detection from Fewer Data ICLR 2023
Towards Few-Annotation Learning for Object Detection: Are Transformer-Based Models More Efficient? WACV 2023
Improving Few-Shot Learning through Multi-task Representation Learning Theory ECCV 2022
A PAC-Bayes Analysis of Adversarial Robustness NIPS 2021
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound NIPS 2021
Learning from Few Positives: a Provably Accurate Metric Learning Algorithm to Deal with Imbalanced Data IJCAI 2020
Differentially Private Optimal Transport: Application to Domain Adaptation IJCAI 2019
From Cost-Sensitive Classification to Tight F-measure Bounds AISTATS 2019
Near-Lossless Binarization of Word Embeddings AAAI 2019
Joint distribution optimal transportation for domain adaptation NIPS 2017
Dict2vec : Learning Word Embeddings using Lexical Dictionaries EMNLP 2017
Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning JMLR 2016
Mapping Estimation for Discrete Optimal Transport NIPS 2016
A New PAC-Bayesian Perspective on Domain Adaptation ICML 2016
Regressive Virtual Metric Learning NIPS 2015
A Theoretical Analysis of Metric Hypothesis Transfer Learning ICML 2015
Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning ICML 2014
A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers ICML 2013
Unsupervised Visual Domain Adaptation Using Subspace Alignment ICCV 2013
Using Contextual Representations to Efficiently Learn Context-Free Languages JMLR 2010