Dieuleveut, Aymeric

30 publications

TMLR 2026 Byzantine-Robust Gossip: Insights from a Dual Approach Renaud Gaucher, Hadrien Hendrikx, Aymeric Dieuleveut

AISTATS 2025 Refined Analysis of Constant Step Size Federated Averaging and Federated Richardson-Romberg Extrapolation Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines

ICML 2025 Scaffold with Stochastic Gradients: New Analysis with Linear Speed-up Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Eric Moulines

NeurIPS 2025 Tight Analyses of First-Order Methods with Error Feedback Daniel Berg Thomsen, Adrien Taylor, Aymeric Dieuleveut

ICML 2025 Unified Breakdown Analysis for Byzantine Robust Gossip Renaud Gaucher, Aymeric Dieuleveut, Hadrien Hendrikx

NeurIPS 2025 Valid Selection Among Conformal Sets Mahmoud Hegazy, Liviu Aolaritei, Michael I. Jordan, Aymeric Dieuleveut

JMLR 2024 Compressed and Distributed Least-Squares Regression: Convergence Rates with Applications to Federated Learning Constantin Philippenko, Aymeric Dieuleveut

AISTATS 2024 Compression with Exact Error Distribution for Federated Learning Mahmoud Hegazy, Rémi Leluc, Cheuk Ting Li, Aymeric Dieuleveut

AISTATS 2024 Proving Linear Mode Connectivity of Neural Networks via Optimal Transport Damien Ferbach, Baptiste Goujaud, Gauthier Gidel, Aymeric Dieuleveut

ICML 2024 Random Features Models: A Way to Study the Success of Naive Imputation Alexis Ayme, Claire Boyer, Aymeric Dieuleveut, Erwan Scornet

ICML 2024 Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates Rémi Leluc, Aymeric Dieuleveut, François Portier, Johan Segers, Aigerim Zhuman

ICML 2023 Conformal Prediction with Missing Values Margaux Zaffran, Aymeric Dieuleveut, Julie Josse, Yaniv Romano

ICML 2023 Naive Imputation Implicitly Regularizes High-Dimensional Linear Models Alexis Ayme, Claire Boyer, Aymeric Dieuleveut, Erwan Scornet

AISTATS 2022 Differentially Private Federated Learning on Heterogeneous Data Maxence Noble, Aurélien Bellet, Aymeric Dieuleveut

AISTATS 2022 QLSD: Quantised Langevin Stochastic Dynamics for Bayesian Federated Learning Maxime Vono, Vincent Plassier, Alain Durmus, Aymeric Dieuleveut, Eric Moulines

AISTATS 2022 Super-Acceleration with Cyclical Step-Sizes Baptiste Goujaud, Damien Scieur, Aymeric Dieuleveut, Adrien B. Taylor, Fabian Pedregosa

ICML 2022 Adaptive Conformal Predictions for Time Series Margaux Zaffran, Olivier Feron, Yannig Goude, Julie Josse, Aymeric Dieuleveut

NeurIPS 2022 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, Regis Loeb, Paul Mangold, Tanguy Marchand, Othmane Marfoq, Erum Mushtaq, Boris Muzellec, Constantin Philippenko, Santiago Silva, Maria Teleńczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux

ICML 2022 Near-Optimal Rate of Consistency for Linear Models with Missing Values Alexis Ayme, Claire Boyer, Aymeric Dieuleveut, Erwan Scornet

NeurIPSW 2022 Quadratic Minimization: From Conjugate Gradients to an Adaptive Heavy-Ball Method with Polyak Step-Sizes Baptiste Goujaud, Adrien Taylor, Aymeric Dieuleveut

NeurIPS 2021 Federated-EM with Heterogeneity Mitigation and Variance Reduction Aymeric Dieuleveut, Gersende Fort, Eric Moulines, Geneviève Robin

NeurIPS 2021 Preserved Central Model for Faster Bidirectional Compression in Distributed Settings Constantin Philippenko, Aymeric Dieuleveut

AISTATS 2020 Context Mover’s Distance & Barycenters: Optimal Transport of Contexts for Building Representations Sidak Pal Singh, Andreas Hug, Aymeric Dieuleveut, Martin Jaggi

NeurIPS 2020 Debiasing Averaged Stochastic Gradient Descent to Handle Missing Values Aude Sportisse, Claire Boyer, Aymeric Dieuleveut, Julie Josse

ICML 2020 On Convergence-Diagnostic Based Step Sizes for Stochastic Gradient Descent Scott Pesme, Aymeric Dieuleveut, Nicolas Flammarion

NeurIPS 2019 Communication Trade-Offs for Local-SGD with Large Step Size Aymeric Dieuleveut, Kumar Kshitij Patel

ICLRW 2019 Context Mover's Distance & Barycenters: Optimal Transport of Contexts for Building Representations Sidak Pal Singh, Andreas Hug, Aymeric Dieuleveut, Martin Jaggi

NeurIPS 2019 Unsupervised Scalable Representation Learning for Multivariate Time Series Jean-Yves Franceschi, Aymeric Dieuleveut, Martin Jaggi

ICLRW 2019 Unsupervised Scalable Representation Learning for Multivariate Time Series Jean-Yves Franceschi, Aymeric Dieuleveut, Martin Jaggi

JMLR 2017 Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression Aymeric Dieuleveut, Nicolas Flammarion, Francis Bach