Aymeric Dieuleveut

Publications

Article dans une revue (7)

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 Tayloret al. Mathematical Programming Computation, 2024, 16 (3), pp.337-367. ⟨10.1007/s12532-024-00259-7⟩ Article dans une revue hal-03780353v1
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
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
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
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

Communication dans un congrès (18)

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
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
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
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
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
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
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
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
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 Heet al. NeurIPS 2022 - Thirty-sixth Conference on Neural Information Processing Systems, Nov 2022, New Orleans, United States Communication dans un congrès hal-03900026v1
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
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
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
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
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
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
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
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
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

Poster de conférence (1)

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

Pré-publication, Document de travail (9)

Federated Majorize-Minimization: Beyond Parameter Aggregation Aymeric Dieuleveut,Gersende Fort,Mahmoud Hegazy,Hoi-To Wai 2025 Pré-publication, Document de travail hal-05189632v1
Open Problem: Two Riddles in Heavy-Ball Dynamics Baptiste Goujaud,Adrien Taylor,Aymeric Dieuleveut 2025 Pré-publication, Document de travail hal-05461110v1
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
Byzantine-Robust Gossip: Insights from a Dual Approach Renaud Gaucher,Aymeric Dieuleveut,Hadrien Hendrikx 2025 Pré-publication, Document de travail hal-05466812v1
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
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
Differentially Private Federated Learning on Heterogeneous Data Maxence Noble,Aurélien Bellet,Aymeric Dieuleveut 2021 Pré-publication, Document de travail hal-03498158v1
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

Thèse (1)

Stochastic approximation in Hilbert spaces Aymeric Dieuleveut Statistics [math.ST]. Université Paris sciences et lettres, 2017. English. ⟨NNT : 2017PSLEE059⟩ Thèse tel-01705522v2

HDR (1)

Contributions to Federated Learning and First-Order Optimization Aymeric Dieuleveut Statistics [math.ST]. Institut Polytechnique de Paris, 2023 HDR tel-04554829v1