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papers

Publications (80)

cs.LG2026

Adaptive Personalized Federated Learning via Multi-task Averaging of Kernel Mean Embeddings

Jean-Baptiste Fermanian, Batiste Le Bars, Aurélien Bellet

cs.LG2014

A Survey on Metric Learning for Feature Vectors and Structured Data

Aurélien Bellet, Amaury Habrard, Marc Sebban

cs.LG2024

Privacy Attacks in Decentralized Learning

Abdellah El Mrini, Edwige Cyffers, Aurélien Bellet

cs.LG2026

Private Rate-Constrained Optimization with Applications to Fair Learning

Mohammad Yaghini, Tudor Cebere, Michael Menart +2

cs.LG2026

Unveiling the Non-Monotonic Effect of Privacy on Generalization under Byzantine Robustness

Thomas Boudou, Batiste Le Bars, Nirupam Gupta +1

cs.LG2018

Personalized and Private Peer-to-Peer Machine Learning

Aurélien Bellet, Rachid Guerraoui, Mahsa Taziki +1

cs.CR2022

An Accurate, Scalable and Verifiable Protocol for Federated Differentially Private Averaging

César Sabater, Aurélien Bellet, Jan Ramon

cs.LG2022

Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data

Batiste Le Bars, Aurélien Bellet, Marc Tommasi +2

cs.LG2023

FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings

Jean Ogier du Terrail, Samy-Safwan Ayed, Edwige Cyffers +21

cs.LG2024

Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm

Batiste Le Bars, Aurélien Bellet, Marc Tommasi +2

stat.ML2016

Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions

Igor Colin, Aurélien Bellet, Joseph Salmon +1

cs.DC2015

A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning

Aurélien Bellet, Yingyu Liang, Alireza Bagheri Garakani +2

cs.LG2025

Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model

Tudor Cebere, Aurélien Bellet, Nicolas Papernot

cs.CL2019

Privacy-Preserving Adversarial Representation Learning in ASR: Reality or Illusion?

Brij Mohan Lal Srivastava, Aurélien Bellet, Marc Tommasi +1

cs.CR2026

Privacy in Theory, Bugs in Practice: Grey-Box Auditing of Differential Privacy Libraries

Tudor Cebere, David Erb, Damien Desfontaines +2

cs.LG2026

Unified Privacy Guarantees for Decentralized Learning via Matrix Factorization

Aurélien Bellet, Edwige Cyffers, Davide Frey +3

cs.LG2023

Fair Without Leveling Down: A New Intersectional Fairness Definition

Gaurav Maheshwari, Aurélien Bellet, Pascal Denis +1

cs.LG2021

Advances and Open Problems in Federated Learning

Peter Kairouz, H. Brendan McMahan, Brendan Avent +56

stat.ML2015

Extending Gossip Algorithms to Distributed Estimation of U-Statistics

Igor Colin, Aurélien Bellet, Joseph Salmon +1

stat.ML2025

Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis

Rémi Khellaf, Aurélien Bellet, Julie Josse

cs.IR2022

PEPPER: Empowering User-Centric Recommender Systems over Gossip Learning

Yacine Belal, Aurélien Bellet, Sonia Ben Mokhtar +1

stat.ML2026

Differentially Private and Federated Structure Learning in Bayesian Networks

Ghita Fassy El Fehri, Aurélien Bellet, Philippe Bastien

stat.ML2020

Private Protocols for U-Statistics in the Local Model and Beyond

James Bell, Aurélien Bellet, Adrià Gascón +1

stat.ML2026

Optimal Transport under Group Fairness Constraints

Linus Bleistein, Mathieu Dagréou, Francisco Andrade +2

cs.LG2018

Hiding in the Crowd: A Massively Distributed Algorithm for Private Averaging with Malicious Adversaries

Pierre Dellenbach, Aurélien Bellet, Jan Ramon

cs.CR2024

Rényi Pufferfish Privacy: General Additive Noise Mechanisms and Privacy Amplification by Iteration

Clément Pierquin, Aurélien Bellet, Marc Tommasi +1

cs.SD2022

Differentially Private Speaker Anonymization

Ali Shahin Shamsabadi, Brij Mohan Lal Srivastava, Aurélien Bellet +5

eess.AS2020

Design Choices for X-vector Based Speaker Anonymization

Brij Mohan Lal Srivastava, Natalia Tomashenko, Xin Wang +5

cs.LG2025

Privacy Amplification Through Synthetic Data: Insights from Linear Regression

Clément Pierquin, Aurélien Bellet, Marc Tommasi +1

cs.LG2026

Model Agnostic Differentially Private Causal Inference

Christian Janos Lebeda, Mathieu Even, Aurélien Bellet +1

cs.LG2023

Differentially Private Federated Learning on Heterogeneous Data

Maxence Noble, Aurélien Bellet, Aymeric Dieuleveut

cs.LG2024

Synthetic Data Generation for Intersectional Fairness by Leveraging Hierarchical Group Structure

Gaurav Maheshwari, Aurélien Bellet, Pascal Denis +1

stat.ML2021

Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints

Robin Vogel, Aurélien Bellet, Stephan Clémençon

cs.LG2022

Federated Multi-Task Learning under a Mixture of Distributions

Othmane Marfoq, Giovanni Neglia, Aurélien Bellet +2

cs.LG2017

Decentralized Collaborative Learning of Personalized Models over Networks

Paul Vanhaesebrouck, Aurélien Bellet, Marc Tommasi

cs.LG2024

Differentially Private Decentralized Learning with Random Walks

Edwige Cyffers, Aurélien Bellet, Jalaj Upadhyay

cs.CR2026

Privacy Auditing with Zero (0) Training Run

Tudor Cebere, Mathieu Even, Linus Bleistein +1

cs.LG2022

Differentially Private Coordinate Descent for Composite Empirical Risk Minimization

Paul Mangold, Aurélien Bellet, Joseph Salmon +1

cs.DC2018

A Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm

Wenjie Zheng, Aurélien Bellet, Patrick Gallinari

stat.ML2026

Principled Federated Random Forests for Heterogeneous Data

Rémi Khellaf, Erwan Scornet, Aurélien Bellet +1

cs.LG2024

The Relative Gaussian Mechanism and its Application to Private Gradient Descent

Hadrien Hendrikx, Paul Mangold, Aurélien Bellet

cs.CL2020

Evaluating Voice Conversion-based Privacy Protection against Informed Attackers

Brij Mohan Lal Srivastava, Nathalie Vauquier, Md Sahidullah +3

stat.ML2025

Optimal Transport with Heterogeneously Missing Data

Linus Bleistein, Aurélien Bellet, Julie Josse

math.ST2024

Marginal and training-conditional guarantees in one-shot federated conformal prediction

Pierre Humbert, Batiste Le Bars, Aurélien Bellet +1

cs.LG2020

Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs

Valentina Zantedeschi, Aurélien Bellet, Marc Tommasi

cs.LG2013

Supervised Metric Learning with Generalization Guarantees

Aurélien Bellet

cs.LG2023

High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent

Paul Mangold, Aurélien Bellet, Joseph Salmon +1

stat.ML2017

Kernel Approximation Methods for Speech Recognition

Avner May, Alireza Bagheri Garakani, Zhiyun Lu +9

cs.LG2025

Federated Learning for MRI-based BrainAGE: a multicenter study on post-stroke functional outcome prediction

Vincent Roca, Marc Tommasi, Paul Andrey +8

cs.LG2023

Differential Privacy has Bounded Impact on Fairness in Classification

Paul Mangold, Michaël Perrot, Aurélien Bellet +1

cs.LG2014

Sparse Compositional Metric Learning

Yuan Shi, Aurélien Bellet, Fei Sha

cs.LG2026

Lumberjack: Better Differentially Private Random Forests through Heavy Hitter Detection in Trees

Christian Janos Lebeda, David Erb, Tudor Cebere +1

stat.ML2019

Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning

Robin Vogel, Aurélien Bellet, Stephan Clémençon +2

stat.ML2016

Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics

Stéphan Clémençon, Aurélien Bellet, Igor Colin

cs.LG2026

On Gossip Algorithms for Machine Learning with Pairwise Objectives

Igor Colin, Aurélien Bellet, Stephan Clémençon +1

stat.ML2023

One-Shot Federated Conformal Prediction

Pierre Humbert, Batiste Le Bars, Aurélien Bellet +1

cs.CR2026

Privacy Amplification Persists under Unlimited Synthetic Data Release

Clément Pierquin, Aurélien Bellet, Marc Tommasi +1

cs.LG2022

Collaborative Algorithms for Online Personalized Mean Estimation

Mahsa Asadi, Aurélien Bellet, Odalric-Ambrym Maillard +1

cs.LG2026

Loss Gap Parity for Fairness in Heterogeneous Federated Learning

Brahim Erraji, Michaël Perrot, Aurélien Bellet

cs.LG2015

How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets

Zhiyun Lu, Avner May, Kuan Liu +8

cs.CR2024

Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging

Edwige Cyffers, Mathieu Even, Aurélien Bellet +1

stat.ME2026

Causal Meta-Analysis: Rethinking the Foundations of Evidence-Based Medicine

Clément Berenfeld, Ahmed Boughdiri, Bénédicte Colnet +5

cs.LG2022

GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation

Sina Sajadmanesh, Ali Shahin Shamsabadi, Aurélien Bellet +1

cs.LG2026

Tight Stability Bounds for Robust Distributed Learning: Byzantine Failures Hurt Generalization More than Data Poisoning

Thomas Boudou, Batiste Le Bars, Nirupam Gupta +1

cs.CL2022

Fair NLP Models with Differentially Private Text Encoders

Gaurav Maheshwari, Pascal Denis, Mikaela Keller +1

cs.LG2026

Dangerous Liaisons of Convex Learning and Non-Affine Aggregation

Thomas Boudou, Batiste Le Bars, Nirupam Gupta +1

cs.LG2026

Causal Evaluation of Membership Inference Attacks

Mathieu Even, Clément Berenfeld, Linus Bleistein +3

cs.LG2014

Robustness and Generalization for Metric Learning

Aurélien Bellet, Amaury Habrard

stat.ML2019

Escaping the Curse of Dimensionality in Similarity Learning: Efficient Frank-Wolfe Algorithm and Generalization Bounds

Kuan Liu, Aurélien Bellet

cs.DC2020

Who started this rumor? Quantifying the natural differential privacy guarantees of gossip protocols

Aurélien Bellet, Rachid Guerraoui, Hadrien Hendrikx

cs.LG2021

D-Cliques: Compensating for Data Heterogeneity with Topology in Decentralized Federated Learning

Aurélien Bellet, Anne-Marie Kermarrec, Erick Lavoie

cs.LG2022

Privacy Amplification by Decentralization

Edwige Cyffers, Aurélien Bellet

stat.ML2018

A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization

Robin Vogel, Aurélien Bellet, Stéphan Clémençon

cs.CR2021

Mitigating Leakage from Data Dependent Communications in Decentralized Computing using Differential Privacy

Riad Ladjel, Nicolas Anciaux, Aurélien Bellet +1

cs.LG2020

metric-learn: Metric Learning Algorithms in Python

William de Vazelhes, CJ Carey, Yuan Tang +2

cs.LG2026

Detectability in Diversity: Improved Canary Crafting for Privacy Auditing in One Run

Mathieu Dagréou, Aurélien Bellet

cs.LG2023

From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning

Edwige Cyffers, Aurélien Bellet, Debabrota Basu

stat.ME2026

Federated Causal Inference from Multi-Site Observational Data via Propensity Score Aggregation

Rémi Khellaf, Aurélien Bellet, Julie Josse

cs.LG2019

Similarity Learning for High-Dimensional Sparse Data

Kuan Liu, Aurélien Bellet, Fei Sha

cs.CR2025

Nebula: Efficient, Private and Accurate Histogram Estimation

Ali Shahin Shamsabadi, Peter Snyder, Ralph Giles +2