Aymeric Dieuleveut

37
Documents

Publications

Publications

Provable non-accelerations of the heavy-ball method

Baptiste Goujaud , Adrien Taylor , Aymeric Dieuleveut

Mathematical Programming, 2025, ⟨10.1007/s10107-025-02269-2⟩

Article dans une revue hal-04384188v1

PEPit: computer-assisted worst-case analyses of first-order optimization methods in Python

Baptiste Goujaud , Céline Moucer , François Glineur , Julien Hendrickx , Adrien Taylor et al.

Mathematical Programming Computation, 2024, 16 (3), pp.337-367. ⟨10.1007/s12532-024-00259-7⟩

Article dans une revue hal-03780353v1
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Stochastic Approximation Beyond Gradient for Signal Processing and Machine Learning

Aymeric Dieuleveut , Gersende Fort , Eric Moulines , Hoi-To Wai

IEEE Transactions on Signal Processing, 2023, 71, pp.3117-3148. ⟨10.1109/TSP.2023.3301121⟩

Article dans une revue hal-03979922v1

Counter-Examples in First-Order Optimization: A Constructive Approach

Baptiste Goujaud , Aymeric Dieuleveut , Adrien Taylor

IEEE Control Systems Letters, 2023, 7, pp.2485-2490. ⟨10.1109/LCSYS.2023.3286277⟩

Article dans une revue hal-04384238v1
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Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains

Aymeric Dieuleveut , Alain Durmus , Francis Bach

Annals of Statistics, 2020, 48 (3), ⟨10.1214/19-AOS1850⟩

Article dans une revue hal-01565514v2
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Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression

Aymeric Dieuleveut , Nicolas Flammarion , Francis Bach

Journal of Machine Learning Research, 2017, 17 (101), pp.1-51

Article dans une revue hal-01275431v2
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Non-parametric Stochastic Approximation with Large Step sizes

Aymeric Dieuleveut , Francis Bach

Annals of Statistics, 2015, 44 (4), ⟨10.1214/15-AOS1391⟩

Article dans une revue hal-01053831v2
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Tight analyses of first-order methods with error feedback

Daniel Berg Thomsen , Adrien Taylor , Aymeric Dieuleveut

Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS), Dec 2025, San Diego, CA, United States. ⟨10.48550/arXiv.2506.05271⟩

Communication dans un congrès hal-05346805v1
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Proving Linear Mode Connectivity of Neural Networks via Optimal Transport

Damien Ferbach , Baptiste Goujaud , Gauthier Gidel , Aymeric Dieuleveut

27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024), May 2024, Valence, Spain. pp.3853-3861

Communication dans un congrès hal-04554453v1
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Random features models: a way to study the success of naive imputation

Alexis Ayme , Claire Boyer , Aymeric Dieuleveut , Erwan Scornet

International Conference on Machine Learning,, Jul 2024, Vienna, Austria

Communication dans un congrès hal-04440304v1
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On Fundamental Proof Structures in First-Order Optimization

Baptiste Goujaud , Aymeric Dieuleveut , Adrien Taylor

Conference on Decision and Control, Tutorial sessions, Dec 2023, Marina Bay Sands, Singapore. ⟨10.48550/arXiv.2310.02015⟩

Communication dans un congrès hal-04384178v1
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Compression with Exact Error Distribution for Federated Learning

Mahmoud Hegazy , Rémi Leluc , Cheuk Ting Li , Aymeric Dieuleveut

International Conference on Artificial Intelligence and Statistics, May 2024, Valencia (Espagne), Spain. pp.613-621

Communication dans un congrès hal-04554506v1
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Conformal Prediction with Missing Values

Margaux Zaffran , Aymeric Dieuleveut , Julie Josse , Yaniv Romano

ICML 2023 - 40 th International Conference on Machine Learning, Jul 2023, Honolulu (Hawai), United States. pp.40578

Communication dans un congrès hal-03896384v4
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Naive imputation implicitly regularizes high-dimensional linear models

Alexis Ayme , Claire Boyer , Aymeric Dieuleveut , Erwan Scornet

International Conference on Machine Learning, Jul 2023, Hawai, USA, United States

Communication dans un congrès hal-03958825v1
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QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning

Maxime Vono , Vincent Plassier , Alain Durmus , Aymeric Dieuleveut , Eric Moulines

International Conference on Artificial Intelligence and Statistics, 2022, Online, France

Communication dans un congrès hal-03589952v1
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Adaptive Conformal Predictions for Time Series

Margaux Zaffran , Olivier Féron , Yannig Goude , Julie Josse , Aymeric Dieuleveut

ICML 2022 - 39th International Conference on Machine Learning, Jul 2022, Baltimore - Maryland, United States

Communication dans un congrès hal-03573934v2
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Differentially Private Federated Learning on Heterogeneous Data

Maxence Noble , Aurélien Bellet , Aymeric Dieuleveut

Proceedings of The 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 2022, Virtual, Spain

Communication dans un congrès hal-03905078v1

FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings

Jean Ogier Du Terrail , Samy-Safwan Ayed , Edwige Cyffers , Felix Grimberg , Chaoyang He et al.

NeurIPS 2022 - Thirty-sixth Conference on Neural Information Processing Systems, Nov 2022, New Orleans, United States

Communication dans un congrès hal-03900026v1

Super-Acceleration with Cyclical Step-sizes

Baptiste Goujaud , Damien Scieur , Aymeric Dieuleveut , Adrien Taylor , Fabian Pedregosa

International Conference on Artificial Intelligence and Statistics, Mar 2022, Virtual conference, France

Communication dans un congrès hal-03377367v1
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Near-optimal rate of consistency for linear models with missing values

Alexis Ayme , Claire Boyer , Aymeric Dieuleveut , Erwan Scornet

International Conference on Machine Learning,, Jul 2022, Baltimore MD, United States

Communication dans un congrès hal-03552109v2
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Preserved central model for faster bidirectional compression in distributed settings

Constantin Philippenko , Aymeric Dieuleveut

35th Conference on Neural Information Processing Systems, Dec 2021, Virtual-only Conference, France. pp.2387-2399, ⟨10.48550/arXiv.2102.12528⟩

Communication dans un congrès hal-04255271v1
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Federated Expectation Maximization with heterogeneity mitigation and variance reduction

Aymeric Dieuleveut , Gersende Fort , Eric Moulines , Geneviève Robin

NeurIPS 2021 - 35th Conference on Neural Information Processing Systems, Dec 2021, Sydney, Australia. ⟨10.48550/arXiv.2111.02083⟩

Communication dans un congrès hal-03333516v3
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On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent

Scott Pesme , Aymeric Dieuleveut , Nicolas Flammarion

37th International Conference on Machine Learning (ICML 2020), Jul 2020, Vienne (en ligne), Austria. pp.119:7641-7651

Communication dans un congrès hal-04554421v1
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Debiasing Stochastic Gradient Descent to handle missing values

Aude Sportisse , Claire Boyer , Aymeric Dieuleveut , Julie Josse

NeurIPS 2020 - 34th Conference on Neural Information Processing Systems, Dec 2020, Vancouver, Canada

Communication dans un congrès hal-02483651v2
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Unsupervised Scalable Representation Learning for Multivariate Time Series

Jean-Yves Franceschi , Aymeric Dieuleveut , Martin Jaggi

Thirty-third Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, Dec 2019, Vancouver, Canada. pp.4650--4661

Communication dans un congrès hal-01998101v4
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Unsupervised Scalable Representation Learning for Multivariate Time Series

Jean-Yves Franceschi , Aymeric Dieuleveut , Martin Jaggi

Hanna 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

Poster de conférence hal-02320167v2
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Refined Analysis of Federated Averaging's Bias and Federated Richardson-Romberg Extrapolation

Paul Mangold , Alain Durmus , Aymeric Dieuleveut , Sergey Samsonov , Eric Moulines

2025

Pré-publication, Document de travail hal-04878343v1

Open Problem: Two Riddles in Heavy-Ball Dynamics

Baptiste Goujaud , Adrien Taylor , Aymeric Dieuleveut

2025

Pré-publication, Document de travail hal-05461110v1
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Byzantine-Robust Gossip: Insights from a Dual Approach

Renaud Gaucher , Aymeric Dieuleveut , Hadrien Hendrikx

2025

Pré-publication, Document de travail hal-05466812v1
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Federated Majorize-Minimization: Beyond Parameter Aggregation

Aymeric Dieuleveut , Gersende Fort , Mahmoud Hegazy , Hoi-To Wai

2025

Pré-publication, Document de travail hal-05189632v1
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Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates

Rémi Leluc , Aymeric Dieuleveut , François Portier , Johan Segers , Aigerim Zhuman

2024

Pré-publication, Document de travail hal-04438124v1
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Compressed and distributed least-squares regression: convergence rates with applications to Federated Learning

Constantin Philippenko , Aymeric Dieuleveut

2023

Pré-publication, Document de travail hal-04350090v1

Optimal first-order methods for convex functions with a quadratic upper bound

Baptiste Goujaud , Adrien Taylor , Aymeric Dieuleveut

2022

Pré-publication, Document de travail hal-03780321v1
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Differentially Private Federated Learning on Heterogeneous Data

Maxence Noble , Aurélien Bellet , Aymeric Dieuleveut

2021

Pré-publication, Document de travail hal-03498158v1
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Artemis: tight convergence guarantees for bidirectional compression in heterogeneous settings for federated learning

Constantin Philippenko , Aymeric Dieuleveut

2020

Pré-publication, Document de travail hal-04350055v1
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Stochastic approximation in Hilbert spaces

Aymeric Dieuleveut

Statistics [math.ST]. Université Paris sciences et lettres, 2017. English. ⟨NNT : 2017PSLEE059⟩

Thèse tel-01705522v2