Aymeric Dieuleveut
Publications
Publications
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Tight analyses of first-order methods with error feedbackThirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS), Dec 2025, San Diego, CA, United States. ⟨10.48550/arXiv.2506.05271⟩ |
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Proving Linear Mode Connectivity of Neural Networks via Optimal Transport27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), May 2024, Valence, Spain. pp.3853-3861 |
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Random features models: a way to study the success of naive imputationInternational Conference on Machine Learning,, Jul 2024, Vienna, Austria |
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On Fundamental Proof Structures in First-Order OptimizationConference on Decision and Control, Tutorial sessions, Dec 2023, Marina Bay Sands, Singapore. ⟨10.48550/arXiv.2310.02015⟩ |
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Compression with Exact Error Distribution for Federated LearningInternational Conference on Artificial Intelligence and Statistics, May 2024, Valencia (Espagne), Spain. pp.613-621 |
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Conformal Prediction with Missing ValuesICML 2023 - 40 th International Conference on Machine Learning, Jul 2023, Honolulu (Hawai), United States. pp.40578 |
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Naive imputation implicitly regularizes high-dimensional linear modelsInternational Conference on Machine Learning, Jul 2023, Hawai, USA, United States |
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QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated LearningInternational Conference on Artificial Intelligence and Statistics, 2022, Online, France |
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Adaptive Conformal Predictions for Time SeriesICML 2022 - 39th International Conference on Machine Learning, Jul 2022, Baltimore - Maryland, United States |
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Differentially Private Federated Learning on Heterogeneous DataProceedings of The 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 2022, Virtual, Spain |
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FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare SettingsNeurIPS 2022 - Thirty-sixth Conference on Neural Information Processing Systems, Nov 2022, New Orleans, United States |
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Super-Acceleration with Cyclical Step-sizesInternational Conference on Artificial Intelligence and Statistics, Mar 2022, Virtual conference, France |
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Near-optimal rate of consistency for linear models with missing valuesInternational Conference on Machine Learning,, Jul 2022, Baltimore MD, United States |
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Preserved central model for faster bidirectional compression in distributed settings35th Conference on Neural Information Processing Systems, Dec 2021, Virtual-only Conference, France. pp.2387-2399, ⟨10.48550/arXiv.2102.12528⟩ |
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Federated Expectation Maximization with heterogeneity mitigation and variance reductionNeurIPS 2021 - 35th Conference on Neural Information Processing Systems, Dec 2021, Sydney, Australia. ⟨10.48550/arXiv.2111.02083⟩ |
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On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent37th International Conference on Machine Learning (ICML 2020), Jul 2020, Vienne (en ligne), Austria. pp.119:7641-7651 |
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Debiasing Stochastic Gradient Descent to handle missing valuesNeurIPS 2020 - 34th Conference on Neural Information Processing Systems, Dec 2020, Vancouver, Canada |
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Unsupervised Scalable Representation Learning for Multivariate Time SeriesThirty-third Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, Dec 2019, Vancouver, Canada. pp.4650--4661 |
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Unsupervised Scalable Representation Learning for Multivariate Time SeriesHanna Wallach; Hugo Larochelle; Alina Beygelzimer; Florence d'Alché-Buc; Emily Fox; Roman Garnett. Thirty-third Conference on Neural Information Processing Systems, Dec 2019, Vancouver, Canada. Curran Associates, Inc., 32, Advances in Neural Information Processing Systems |
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Stochastic approximation in Hilbert spacesStatistics [math.ST]. Université Paris sciences et lettres, 2017. English. ⟨NNT : 2017PSLEE059⟩ |
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Contributions to Federated Learning and First-Order OptimizationStatistics [math.ST]. Institut Polytechnique de Paris, 2023 |