Amaury Habrard

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

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Achievements

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🗺️ Taxonomy Completionist (43) 🌍 Conference Polyglot · Gold 🏃 Academic Marathon · Full 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird

🧭 Keyword Pioneer 🏆 Grand Slam 🚀 Conference Pioneer 🔥 Unstoppable · Bronze ❓ The Questioner 💎 Century Club · Bronze 📈 Trend Setter 🗃️ Keyword Collector (98)

Venues

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

Top co-authors

Rémi Emonet (6) Emilie Morvant (5) Marc Sebban (5) Pascal Germain (3) Romaric Audigier (3) Quentin Bouniot (3) Paul Viallard (3) Michaël Perrot (3) Angélique Loesch (3) Valentina Zantedeschi (2)

Research topics

Machine Learning (22) Optimization & Theory (14) Core Methods (8) Application Areas (7) Deep Learning (6) Learning Types · Machine Learning (6) Artificial Intelligence (5) Mathematics & Optimization (5) Learning Paradigms (4) Optimization (4) Computer Vision (3) Natural Language Processing (2) Analysis (2) Architectures (2) Learning Types · Deep Learning (2)

Keywords

domain adaptation (6) optimal transport (4) generalization bound (4) transfer learning (4) majority vote (3) metric learning (3) word embedding (2) representation learning (2) weighted automaton (2) hankel matrix (2) few-shot learning (2) spectral learning (2) object detection (2) concentration bound (2) unsupervised learning (2) text classification (2) pac-bayes theory (2) singular value decomposition (2) pac-bayes bound (2) convex optimization (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 NeurIPS 2021 Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound NeurIPS 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 Dict2vec : Learning Word Embeddings using Lexical Dictionaries EMNLP 2017 Joint distribution optimal transportation for domain adaptation NeurIPS 2017 A New PAC-Bayesian Perspective on Domain Adaptation ICML 2016 Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning JMLR 2016 Mapping Estimation for Discrete Optimal Transport NeurIPS 2016 A Theoretical Analysis of Metric Hypothesis Transfer Learning ICML 2015 Regressive Virtual Metric Learning NeurIPS 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