| 2025 | AISTATS | Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis. | Rmi Khellaf, Aurlien Bellet, Julie Josse |
| 2025 | CCS | Untitled record | Ali Shahin Shamsabadi, Peter Snyder, Ralph Giles, Aurlien Bellet, Hamed Haddadi |
| 2025 | ICLR | Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model. | Tudor Ioan Cebere, Aurlien Bellet, Nicolas Papernot |
| 2025 | ICML | Privacy Amplification Through Synthetic Data: Insights from Linear Regression. | Clment Pierquin, Aurlien Bellet, Marc Tommasi, Matthieu Boussard |
| 2024 | AISTATS | The Relative Gaussian Mechanism and its Application to Private Gradient Descent. | Hadrien Hendrikx, Paul Mangold, Aurlien Bellet |
| 2024 | ICLR | DP-SGD Without Clipping: The Lipschitz Neural Network Way. | Louis Bthune, Thomas Massena, Thibaut Boissin, Aurlien Bellet, Franck Mamalet, Yannick Prudent, Corentin Friedrich, Mathieu Serrurier, David Vigouroux |
| 2024 | ICLR | Confidential-DPproof: Confidential Proof of Differentially Private Training. | Ali Shahin Shamsabadi, Gefei Tan, Tudor Cebere, Aurlien Bellet, Hamed Haddadi, Nicolas Papernot, Xiao Wang, Adrian Weller |
| 2024 | ICML | Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm. | Batiste Le Bars, Aurlien Bellet, Marc Tommasi, Kevin Scaman, Giovanni Neglia |
| 2024 | ICML | Differentially Private Decentralized Learning with Random Walks. | Edwige Cyffers, Aurlien Bellet, Jalaj Upadhyay |
| 2024 | ICML | Privacy Attacks in Decentralized Learning. | Abdellah El Mrini, Edwige Cyffers, Aurlien Bellet |
| 2024 | ICML | Rnyi Pufferfish Privacy: General Additive Noise Mechanisms and Privacy Amplification by Iteration via Shift Reduction Lemmas. | Clment Pierquin, Aurlien Bellet, Marc Tommasi, Matthieu Boussard |
| 2023 | AISTATS | Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data. | Batiste Le Bars, Aurlien Bellet, Marc Tommasi, Erick Lavoie, Anne-Marie Kermarrec |
| 2023 | AISTATS | High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent. | Paul Mangold, Aurlien Bellet, Joseph Salmon, Marc Tommasi |
| 2023 | EMNLP | Fair Without Leveling Down: A New Intersectional Fairness Definition. | Gaurav Maheshwari, Aurlien Bellet, Pascal Denis, Mikaela Keller |
| 2023 | ICML | From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning. | Edwige Cyffers, Aurlien Bellet, Debabrota Basu |
| 2023 | ICML | One-Shot Federated Conformal Prediction. | Pierre Humbert, Batiste Le Bars, Aurlien Bellet, Sylvain Arlot |
| 2023 | ICML | Differential Privacy has Bounded Impact on Fairness in Classification. | Paul Mangold, Michal Perrot, Aurlien Bellet, Marc Tommasi |
| 2022 | AISTATS | Privacy Amplification by Decentralization. | Edwige Cyffers, Aurlien Bellet |
| 2022 | AISTATS | Differentially Private Federated Learning on Heterogeneous Data. | Maxence Noble, Aurlien Bellet, Aymeric Dieuleveut |
| 2022 | EMNLP | Fair NLP Models with Differentially Private Text Encoders. | Gaurav Maheshwari, Pascal Denis, Mikaela Keller, Aurlien Bellet |
| 2022 | ICML | Differentially Private Coordinate Descent for Composite Empirical Risk Minimization. | Paul Mangold, Aurlien Bellet, Joseph Salmon, Marc Tommasi |
| 2022 | Interspeech | Enhancing Speech Privacy with Slicing. | Mohamed Maouche, Brij Mohan Lal Srivastava, Nathalie Vauquier, Aurlien Bellet, Marc Tommasi, Emmanuel Vincent |
| 2022 | SRDS | D-Cliques: Compensating for Data Heterogeneity with Topology in Decentralized Federated Learning. | Aurlien Bellet, Anne-Marie Kermarrec, Erick Lavoie |
| 2021 | AISTATS | Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints. | Robin Vogel, Aurlien Bellet, Stphan Clmenon |
| 2020 | AISTATS | Private Protocols for U-Statistics in the Local Model and Beyond. | James Bell, Aurlien Bellet, Adri Gascn, Tejas Kulkarni |
| 2020 | AISTATS | Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs. | Valentina Zantedeschi, Aurlien Bellet, Marc Tommasi |
| 2020 | ICASSP | Evaluating Voice Conversion-Based Privacy Protection against Informed Attackers. | Brij Mohan Lal Srivastava, Nathalie Vauquier, Md. Sahidullah, Aurlien Bellet, Marc Tommasi, Emmanuel Vincent |
| 2020 | Interspeech | A Comparative Study of Speech Anonymization Metrics. | Mohamed Maouche, Brij Mohan Lal Srivastava, Nathalie Vauquier, Aurlien Bellet, Marc Tommasi, Emmanuel Vincent |
| 2020 | Interspeech | Design Choices for X-Vector Based Speaker Anonymization. | Brij Mohan Lal Srivastava, Natalia A. Tomashenko, Xin Wang, Emmanuel Vincent, Junichi Yamagishi, Mohamed Maouche, Aurlien Bellet, Marc Tommasi |
| 2020 | RECOMB | Reconstructing Genotypes in Private Genomic Databases from Genetic Risk Scores. | Brooks Paige, James Bell, Aurlien Bellet, Adri Gascn, Daphne Ezer |
| 2019 | Interspeech | Privacy-Preserving Adversarial Representation Learning in ASR: Reality or Illusion? | Brij Mohan Lal Srivastava, Aurlien Bellet, Marc Tommasi, Emmanuel Vincent |
| 2018 | AISTATS | Personalized and Private Peer-to-Peer Machine Learning. | Aurlien Bellet, Rachid Guerraoui, Mahsa Taziki, Marc Tommasi |
| 2018 | EMNLP | A Probabilistic Model for Joint Learning of Word Embeddings from Texts and Images. | Melissa Ailem, Bowen Zhang, Aurlien Bellet, Pascal Denis, Fei Sha |
| 2018 | ICML | A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization. | Robin Vogel, Aurlien Bellet, Stphan Clmenon |
| 2017 | AISTATS | Decentralized Collaborative Learning of Personalized Models over Networks. | Paul Vanhaesebrouck, Aurlien Bellet, Marc Tommasi |
| 2016 | ICASSP | A comparison between deep neural nets and kernel acoustic models for speech recognition. | Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurlien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha |
| 2016 | ICML | Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions. | Igor Colin, Aurlien Bellet, Joseph Salmon, Stphan Clmenon |
| 2015 | AISTATS | Similarity Learning for High-Dimensional Sparse Data. | Kuan Liu, Aurlien Bellet, Fei Sha |
| 2015 | SDM | A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning. | Aurlien Bellet, Yingyu Liang, Alireza Bagheri Garakani, Maria-Florina Balcan, Fei Sha |
| 2014 | AAAI | Sparse Compositional Metric Learning. | Yuan Shi, Aurlien Bellet, Fei Sha |
| 2012 | ICML | Similarity Learning for Provably Accurate Sparse Linear Classification. | Aurlien Bellet, Amaury Habrard, Marc Sebban |
| 2011 | ICTAI | An Experimental Study on Learning with Good Edit Similarity Functions. | Aurlien Bellet, Marc Sebban, Amaury Habrard |