Paul Mangold - RankMe

27 papers A* 5A 4Journal 15Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Softmax and Entropy: Improving Convergence Guarantees of Policy Gradients by f-SoftArgmax Parameterization with Coupled Regularization. CoRR Safwan Labbi, Daniil Tiapkin, Paul Mangold, Eric Moulines
2026	J	`jnl`	Learning with Locally Private Examples by Inverse Weierstrass Private Stochastic Gradient Descent. CoRR Jean Dufraiche, Paul Mangold, Michaël Perrot, Marc Tommasi
2026	J	`jnl`	Tight Analysis of Decentralized SGD: A Markov Chain Perspective. CoRR Lucas Versini, Paul Mangold, Aymeric Dieuleveut
2025	J	`jnl`	Convergence Guarantees for Federated SARSA with Local Training and Heterogeneous Agents. CoRR Paul Mangold, Eloïse Berthier, Eric Moulines
2025	A	`conf`	Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents. AISTATS Safwan Labbi, Daniil Tiapkin, Lorenzo Mancini, Paul Mangold, Eric Moulines
2025	J	`jnl`	On Global Convergence Rates for Federated Policy Gradient under Heterogeneous Environment. CoRR Safwan Labbi, Paul Mangold, Daniil Tiapkin, Eric Moulines
2025	A	`conf`	Refined Analysis of Constant Step Size Federated Averaging and Federated Richardson-Romberg Extrapolation. AISTATS Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines
2025	A*	`conf`	Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up. ICML Paul Mangold, Alain Oliviero Durmus, Aymeric Dieuleveut, Eric Moulines
2025	J	`jnl`	Scaffold with Stochastic Gradients: New Analysis with Linear Speed-Up. CoRR Paul Mangold, Alain Durmus, Aymeric Dieuleveut, Eric Moulines
2024	J	`jnl`	Federated UCBVI: Communication-Efficient Federated Regret Minimization with Heterogeneous Agents. CoRR Safwan Labbi, Daniil Tiapkin, Lorenzo Mancini, Paul Mangold, Eric Moulines
2024	J	`jnl`	Joint Channel Selection using FedDRL in V2X. CoRR Lorenzo Mancini, Safwan Labbi, Karim Abed-Meraim, Fouzi Boukhalfa, Alain Durmus, Paul Mangold, Eric Moulines
2024	J	`jnl`	Refined Analysis of Federated Averaging's Bias and Federated Richardson-Romberg Extrapolation. CoRR Paul Mangold, Alain Durmus, Aymeric Dieuleveut, Sergey Samsonov, Eric Moulines
2024	J	`jnl`	SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning. CoRR Paul Mangold, Sergey Samsonov, Safwan Labbi, Ilya Levin, Réda Alami, Alexey Naumov, Eric Moulines
2024	A*	`conf`	SCAFFLSA: Taming Heterogeneity in Federated Linear Stochastic Approximation and TD Learning. NeurIPS Paul Mangold, Sergey Samsonov, Safwan Labbi, Ilya Levin, Réda Alami, Alexey Naumov, Eric Moulines
2024	A	`conf`	The Relative Gaussian Mechanism and its Application to Private Gradient Descent. AISTATS Hadrien Hendrikx, Paul Mangold, Aurélien Bellet
2023	A*	`conf`	Differential Privacy has Bounded Impact on Fairness in Classification. ICML Paul Mangold, Michaël Perrot, Aurélien Bellet, Marc Tommasi
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
2023	A	`conf`	High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent. AISTATS Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
2023	J	`jnl`	The Relative Gaussian Mechanism and its Application to Private Gradient Descent. CoRR Hadrien Hendrikx, Paul Mangold, Aurélien Bellet
2022	A*	`conf`	Differentially Private Coordinate Descent for Composite Empirical Risk Minimization. ICML Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
2022	A*	`conf`	FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. NeurIPS 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
2022	J	`jnl`	FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. CoRR 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
2022	J	`jnl`	Fairness Certificates for Differentially Private Classification. CoRR Paul Mangold, Michaël Perrot, Aurélien Bellet, Marc Tommasi
2022	J	`jnl`	High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent. CoRR Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
2021	J	`jnl`	Differentially Private Coordinate Descent for Composite Empirical Risk Minimization. CoRR Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
2021	—	`conf`	Specifications for the Routine Implementation of Federated Learning in Hospitals Networks. MIE Antoine Lamer, Alexandre Filiot, Yannick Bouillard, Paul Mangold, Paul Andrey, Jessica Schiro
2020	—	`conf`	A Decentralized Framework for Biostatistics and Privacy Concerns. EFMI-STC Paul Mangold, Alexandre Filiot, Mouhamed Moussa, Vincent Sobanski, Grégoire Ficheur, Paul Andrey, Antoine Lamer