Paul Mangold

According to our database, Paul Mangold authored at least 21 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Learning with Locally Private Examples by Inverse Weierstrass Private Stochastic Gradient Descent.

Jean Dufraiche, Paul Mangold, Michaël Perrot, Marc Tommasi

CoRR, February, 2026

Beyond Softmax and Entropy: Improving Convergence Guarantees of Policy Gradients by f-SoftArgmax Parameterization with Coupled Regularization.

Safwan Labbi, Daniil Tiapkin, Paul Mangold, Eric Moulines

CoRR, January, 2026

Tight Analysis of Decentralized SGD: A Markov Chain Perspective.

Lucas Versini, Paul Mangold, Aymeric Dieuleveut

CoRR, January, 2026

2025

Convergence Guarantees for Federated SARSA with Local Training and Heterogeneous Agents.

Paul Mangold, Eloïse Berthier, Eric Moulines

CoRR, December, 2025

On Global Convergence Rates for Federated Policy Gradient under Heterogeneous Environment.

Safwan Labbi, Paul Mangold, Daniil Tiapkin, Eric Moulines

CoRR, May, 2025

Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up.

Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Eric Moulines

Proceedings of the Forty-second International Conference on Machine Learning, 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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents.

Safwan Labbi, Daniil Tiapkin, Lorenzo Mancini, Paul Mangold, Eric Moulines

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Refined Analysis of Federated Averaging's Bias and Federated Richardson-Romberg Extrapolation.

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

CoRR, 2024

Joint Channel Selection using FedDRL in V2X.

Lorenzo Mancini, Safwan Labbi, Karim Abed-Meraim, Fouzi Boukhalfa, Alain Durmus, Paul Mangold, Eric Moulines

CoRR, 2024

SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning.

Paul Mangold, Sergey Samsonov, Safwan Labbi, Ilya Levin, Réda Alami, Alexey Naumov, Eric Moulines

CoRR, 2024

SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning.

Paul Mangold, Sergey Samsonov, Safwan Labbi, Ilya Levin, Réda Alami, Alexey Naumov, Eric Moulines

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

The Relative Gaussian Mechanism and its Application to Private Gradient Descent.

Hadrien Hendrikx, Paul Mangold, Aurélien Bellet

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Exploiting Problem Structure in Privacy-Preserving Optimization and Machine Learning. (Exploitation de la Structure des Problèmes en Optimisation et en Apprentissage Automatique Respectueux de la Vie Privée).

Paul Mangold

PhD thesis, 2023

Differential Privacy has Bounded Impact on Fairness in Classification.

Paul Mangold, Michaël Perrot, Aurélien Bellet, Marc Tommasi

Proceedings of the International Conference on Machine Learning, 2023

High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent.

Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Fairness Certificates for Differentially Private Classification.

Paul Mangold, Michaël Perrot, Aurélien Bellet, Marc Tommasi

CoRR, 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 Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Differentially Private Coordinate Descent for Composite Empirical Risk Minimization.

Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi

Proceedings of the International Conference on Machine Learning, 2022

2021

Specifications for the Routine Implementation of Federated Learning in Hospitals Networks.

Antoine Lamer, Alexandre Filiot, Yannick Bouillard, Paul Mangold, Paul Andrey, Jessica Schiro

Proceedings of the Public Health and Informatics, 2021

2020

A Decentralized Framework for Biostatistics and Privacy Concerns.

Paul Mangold, Alexandre Filiot, Mouhamed Moussa, Vincent Sobanski, Grégoire Ficheur, Paul Andrey, Antoine Lamer

Proceedings of the Integrated Citizen Centered Digital Health and Social Care - Citizens as Data Producers and Service co-Creators, 2020