Aymeric Dieuleveut

34

Documents

Publications

	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⟩ Journal articles 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⟩ Journal articles hal-04384238v1
	Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains Aymeric Dieuleveut , Alain Durmus , Francis Bach The Annals of Statistics, 2020, 48 (3), ⟨10.1214/19-AOS1850⟩ Journal articles 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 Journal articles hal-01275431v2
	Non-parametric Stochastic Approximation with Large Step sizes Aymeric Dieuleveut , Francis Bach The Annals of Statistics, 2015, 44 (4), ⟨10.1214/15-AOS1391⟩ Journal articles hal-01053831v2

	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 Conference papers hal-04554506v1
	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 Conference papers hal-04554453v1
	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 Conference papers hal-03896384v4
	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 Conference papers hal-03958825v1
	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⟩ Conference papers hal-04384178v1
	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 Conference papers hal-03552109v2
	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 Conference papers 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 He NeurIPS 2022 - Thirty-sixth Conference on Neural Information Processing Systems, Nov 2022, New Orleans, United States Conference papers hal-03900026v1
	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 Conference papers 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 Conference papers hal-03589952v1
	Adaptive Conformal Predictions for Time Series Margaux Zaffran , Olivier Féron , Yannig Goude , Julie Josse , Aymeric Dieuleveut PMLR 2022 - Proceedings of Machine Learning Research, Jul 2022, Baltimor - Maryland, United States Conference papers hal-03573934v2
	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⟩ Conference papers 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⟩ Conference papers 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 Conference papers 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 Conference papers 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 Conference papers hal-01998101v4

	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 Conference poster hal-02320167v2

	Compressed and distributed least-squares regression: convergence rates with applications to Federated Learning Aymeric Dieuleveut , Constantin Philippenko 2024 Preprints, Working Papers, ... hal-04504245v1
	Sliced-Wasserstein Estimation with Spherical Harmonics as Control Variates Rémi Leluc , Aymeric Dieuleveut , François Portier , Johan Segers , Aigerim Zhuman 2024 Preprints, Working Papers, ... hal-04438124v1
	Random features models: a way to study the success of naive imputation Alexis Ayme , Claire Boyer , Aymeric Dieuleveut , Erwan Scornet 2024 Preprints, Working Papers, ... hal-04440304v1
	Compressed and distributed least-squares regression: convergence rates with applications to Federated Learning Aymeric Dieuleveut , Constantin Philippenko 2024 Preprints, Working Papers, ... hal-04504217v1
	Provable non-accelerations of the heavy-ball method Baptiste Goujaud , Adrien Taylor , Aymeric Dieuleveut 2024 Preprints, Working Papers, ... hal-04384188v1
	Compressed and distributed least-squares regression: convergence rates with applications to Federated Learning Constantin Philippenko , Aymeric Dieuleveut 2023 Preprints, Working Papers, ... hal-04350090v1
	Optimal first-order methods for convex functions with a quadratic upper bound Baptiste Goujaud , Adrien Taylor , Aymeric Dieuleveut 2022 Preprints, Working Papers, ... hal-03780321v1
	PEPit: computer-assisted worst-case analyses of first-order optimization methods in Python Baptiste Goujaud , Céline Moucer , François Glineur , Julien Hendrickx , Adrien Taylor 2022 Preprints, Working Papers, ... hal-03780353v1
	Differentially Private Federated Learning on Heterogeneous Data Maxence Noble , Aurélien Bellet , Aymeric Dieuleveut 2021 Preprints, Working Papers, ... hal-03498158v1
	Artemis: tight convergence guarantees for bidirectional compression in heterogeneous settings for federated learning Constantin Philippenko , Aymeric Dieuleveut 2020 Preprints, Working Papers, ... hal-04350055v1

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

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