Bellet, Aurélien

47 publications

AISTATS 2025 Federated Causal Inference: Multi-Study ATE Estimation Beyond Meta-Analysis Rémi Khellaf, Aurélien Bellet, Julie Josse

ICML 2025 Privacy Amplification Through Synthetic Data: Insights from Linear Regression Clément Pierquin, Aurélien Bellet, Marc Tommasi, Matthieu Boussard

ICLR 2025 Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model Tudor Ioan Cebere, Aurélien Bellet, Nicolas Papernot

ICLRW 2024 Confidential-DPproof : Confidential Proof of Differentially Private Training Ali Shahin Shamsabadi, Gefei Tan, Tudor Ioan Cebere, Aurélien Bellet, Hamed Haddadi, Nicolas Papernot, Xiao Wang, Adrian Weller

ICLR 2024 Confidential-DPproof: Confidential Proof of Differentially Private Training Ali Shahin Shamsabadi, Gefei Tan, Tudor Ioan Cebere, Aurélien Bellet, Hamed Haddadi, Nicolas Papernot, Xiao Wang, Adrian Weller

ICLR 2024 DP-SGD Without Clipping: The Lipschitz Neural Network Way Louis Béthune, Thomas Massena, Thibaut Boissin, Aurélien Bellet, Franck Mamalet, Yannick Prudent, Corentin Friedrich, Mathieu Serrurier, David Vigouroux

ICML 2024 Differentially Private Decentralized Learning with Random Walks Edwige Cyffers, Aurélien Bellet, Jalaj Upadhyay

ICML 2024 Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm Batiste Le Bars, Aurélien Bellet, Marc Tommasi, Kevin Scaman, Giovanni Neglia

ICML 2024 Privacy Attacks in Decentralized Learning Abdellah El Mrini, Edwige Cyffers, Aurélien Bellet

ICML 2024 Rényi Pufferfish Privacy: General Additive Noise Mechanisms and Privacy Amplification by Iteration via Shift Reduction Lemmas Clément Pierquin, Aurélien Bellet, Marc Tommasi, Matthieu Boussard

AISTATS 2024 The Relative Gaussian Mechanism and Its Application to Private Gradient Descent Hadrien Hendrikx, Paul Mangold, Aurélien Bellet

ICML 2023 Differential Privacy Has Bounded Impact on Fairness in Classification Paul Mangold, Michaël Perrot, Aurélien Bellet, Marc Tommasi

ICML 2023 From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning Edwige Cyffers, Aurélien Bellet, Debabrota Basu

AISTATS 2023 High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi

ICML 2023 One-Shot Federated Conformal Prediction Pierre Humbert, Batiste Le Bars, Aurélien Bellet, Sylvain Arlot

AISTATS 2023 Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data Batiste Le Bars, Aurélien Bellet, Marc Tommasi, Erick Lavoie, Anne-Marie Kermarrec

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

AISTATS 2022 Privacy Amplification by Decentralization Edwige Cyffers, Aurélien Bellet

MLJ 2022 An Accurate, Scalable and Verifiable Protocol for Federated Differentially Private Averaging César Sabater, Aurélien Bellet, Jan Ramon

TMLR 2022 Collaborative Algorithms for Online Personalized Mean Estimation Mahsa Asadi, Aurélien Bellet, Odalric-Ambrym Maillard, Marc Tommasi

ICML 2022 Differentially Private Coordinate Descent for Composite Empirical Risk Minimization Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi

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

NeurIPS 2022 Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging Edwige Cyffers, Mathieu Even, Aurélien Bellet, Laurent Massoulié

NeurIPSW 2022 Refined Convergence and Topology Learning for Decentralized Optimization with Heterogeneous Data Batiste Le bars, Aurélien Bellet, Marc Tommasi, Erick Lavoie, Anne-marie Kermarrec

AISTATS 2021 Learning Fair Scoring Functions: Bipartite Ranking Under ROC-Based Fairness Constraints Robin Vogel, Aurélien Bellet, Stephan Clémençon

FnTML 2021 Advances and Open Problems in Federated Learning Peter Kairouz, H. Brendan McMahan, Brendan Avent, Aurélien Bellet, Mehdi Bennis, Arjun Nitin Bhagoji, Kallista A. Bonawitz, Zachary Charles, Graham Cormode, Rachel Cummings, Rafael G. L. D'Oliveira, Hubert Eichner, Salim El Rouayheb, David Evans, Josh Gardner, Zachary Garrett, Adrià Gascón, Badih Ghazi, Phillip B. Gibbons, Marco Gruteser, Zaïd Harchaoui, Chaoyang He, Lie He, Zhouyuan Huo, Ben Hutchinson, Justin Hsu, Martin Jaggi, Tara Javidi, Gauri Joshi, Mikhail Khodak, Jakub Konecný, Aleksandra Korolova, Farinaz Koushanfar, Sanmi Koyejo, Tancrède Lepoint, Yang Liu, Prateek Mittal, Mehryar Mohri, Richard Nock, Ayfer Özgür, Rasmus Pagh, Hang Qi, Daniel Ramage, Ramesh Raskar, Mariana Raykova, Dawn Song, Weikang Song, Sebastian U. Stich, Ziteng Sun, Ananda Theertha Suresh, Florian Tramèr, Praneeth Vepakomma, Jianyu Wang, Li Xiong, Zheng Xu, Qiang Yang, Felix X. Yu, Han Yu, Sen Zhao

NeurIPS 2021 Federated Multi-Task Learning Under a Mixture of Distributions Othmane Marfoq, Giovanni Neglia, Aurélien Bellet, Laetitia Kameni, Richard Vidal

AISTATS 2020 Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs Valentina Zantedeschi, Aurélien Bellet, Marc Tommasi

MLOSS 2020 Metric-Learn: Metric Learning Algorithms in Python William de Vazelhes, Cj Carey, Yuan Tang, Nathalie Vauquier, Aurélien Bellet

AISTATS 2020 Private Protocols for U-Statistics in the Local Model and Beyond James Bell, Aurélien Bellet, Adria Gascon, Tejas Kulkarni

JMLR 2019 Kernel Approximation Methods for Speech Recognition Avner May, Alireza Bagheri Garakani, Zhiyun Lu, Dong Guo, Kuan Liu, Aurélien Bellet, Linxi Fan, Michael Collins, Daniel Hsu, Brian Kingsbury, Michael Picheny, Fei Sha

ECML-PKDD 2019 Trade-Offs in Large-Scale Distributed Tuplewise Estimation and Learning Robin Vogel, Aurélien Bellet, Stéphan Clémençon, Ons Jelassi, Guillaume Papa

MLJ 2018 A Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm Wenjie Zheng, Aurélien Bellet, Patrick Gallinari

ICML 2018 A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization Robin Vogel, Aurélien Bellet, Stéphan Clémençon

AISTATS 2018 Personalized and Private Peer-to-Peer Machine Learning Aurélien Bellet, Rachid Guerraoui, Mahsa Taziki, Marc Tommasi

AISTATS 2017 Decentralized Collaborative Learning of Personalized Models over Networks Paul Vanhaesebrouck, Aurélien Bellet, Marc Tommasi

ICML 2016 Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions Igor Colin, Aurelien Bellet, Joseph Salmon, Stéphan Clémençon

NeurIPS 2016 On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability Guillaume Papa, Aurélien Bellet, Stephan Clémençon

JMLR 2016 Scaling-up Empirical Risk Minimization: Optimization of Incomplete $u$-Statistics Stephan Clémençon, Igor Colin, Aurélien Bellet

NeurIPS 2015 Extending Gossip Algorithms to Distributed Estimation of U-Statistics Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon

NeurIPS 2015 SGD Algorithms Based on Incomplete U-Statistics: Large-Scale Minimization of Empirical Risk Guillaume Papa, Stéphan Clémençon, Aurélien Bellet

AISTATS 2015 Similarity Learning for High-Dimensional Sparse Data Kuan Liu, Aurélien Bellet, Fei Sha

MLJ 2014 Learning a Priori Constrained Weighted Majority Votes Aurélien Bellet, Amaury Habrard, Emilie Morvant, Marc Sebban

AAAI 2014 Sparse Compositional Metric Learning Yuan Shi, Aurélien Bellet, Fei Sha

MLJ 2012 Good Edit Similarity Learning by Loss Minimization Aurélien Bellet, Amaury Habrard, Marc Sebban

ICML 2012 Similarity Learning for Provably Accurate Sparse Linear Classification Aurélien Bellet, Amaury Habrard, Marc Sebban

ECML-PKDD 2011 Learning Good Edit Similarities with Generalization Guarantees Aurélien Bellet, Amaury Habrard, Marc Sebban