Aurélien Bellet

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 97

Top Venues

Jean Monnet University, Saint-Étienne, France (PHD)

Education History

Jean Monnet University, Saint-Étienne, France

PHD

Publications

Abdellah El Mrini, Edwige Cyffers, Aurélien Bellet
Privacy Attacks in Decentralized Learning. CoRR (2024)
Edwige Cyffers, Aurélien Bellet, Jalaj Upadhyay
Differentially Private Decentralized Learning with Random Walks. CoRR (2024)
Edwige Cyffers, Aurélien Bellet, Debabrota Basu
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning. CoRR (2023)
Ali Shahin Shamsabadi, Brij Mohan Lal Srivastava, Aurélien Bellet, Nathalie Vauquier, Emmanuel Vincent, Mohamed Maouche, Marc Tommasi, Nicolas Papernot
Differentially Private Speaker Anonymization. Proc. Priv. Enhancing Technol. 2023 (1) (2023)
Gaurav Maheshwari, Aurélien Bellet, Pascal Denis, Mikaela Keller
Fair Without Leveling Down: A New Intersectional Fairness Definition. EMNLP (2023)
Edwige Cyffers, Aurélien Bellet, Debabrota Basu
From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning. ICML (2023)
Gaurav Maheshwari, Aurélien Bellet, Pascal Denis, Mikaela Keller
How to Capture Intersectional Fairness. CoRR (2023)
Sina Sajadmanesh, Ali Shahin Shamsabadi, Aurélien Bellet, Daniel Gatica-Perez
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation. USENIX Security Symposium (2023)
Pierre Humbert, Batiste Le Bars, Aurélien Bellet, Sylvain Arlot
One-Shot Federated Conformal Prediction. ICML (2023)
Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent. AISTATS (2023)
Batiste Le Bars, Aurélien Bellet, Marc Tommasi, Erick Lavoie, Anne-Marie Kermarrec
Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data. AISTATS (2023)
Louis Béthune, Thomas Massena, Thibaut Boissin, Yannick Prudent, Corentin Friedrich, Franck Mamalet, Aurélien Bellet, Mathieu Serrurier, David Vigouroux
DP-SGD Without Clipping: The Lipschitz Neural Network Way. CoRR (2023)
Batiste Le Bars, Aurélien Bellet, Marc Tommasi
Improved Stability and Generalization Analysis of the Decentralized SGD Algorithm. CoRR (2023)
Clément Pierquin, Aurélien Bellet, Marc Tommasi, Matthieu Boussard
Rényi Pufferfish Privacy: General Additive Noise Mechanisms and Privacy Amplification by Iteration. CoRR (2023)
Paul Mangold, Michaël Perrot, Aurélien Bellet, Marc Tommasi
Differential Privacy has Bounded Impact on Fairness in Classification. ICML (2023)
Hadrien Hendrikx, Paul Mangold, Aurélien Bellet
The Relative Gaussian Mechanism and its Application to Private Gradient Descent. CoRR (2023)
Paul Mangold, Michaël Perrot, Aurélien Bellet, Marc Tommasi
Fairness Certificates for Differentially Private Classification. CoRR (2022)
Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization. ICML (2022)
Edwige Cyffers, Aurélien Bellet
Privacy Amplification by Decentralization. AISTATS (2022)
Ali Shahin Shamsabadi, Brij Mohan Lal Srivastava, Aurélien Bellet, Nathalie Vauquier, Emmanuel Vincent, Mohamed Maouche, Marc Tommasi, Nicolas Papernot
Differentially Private Speaker Anonymization. CoRR (2022)
Brij Mohan Lal Srivastava, Mohamed Maouche, Md. Sahidullah, Emmanuel Vincent, Aurélien Bellet, Marc Tommasi, Natalia A. Tomashenko, Xin Wang, Junichi Yamagishi
Privacy and Utility of X-Vector Based Speaker Anonymization. IEEE ACM Trans. Audio Speech Lang. Process. 30 (2022)
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 S. Silva R., Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. CoRR (2022)
Gaurav Maheshwari, Pascal Denis, Mikaela Keller, Aurélien Bellet
Fair NLP Models with Differentially Private Text Encoders. EMNLP (Findings) (2022)
César Sabater, Aurélien Bellet, Jan Ramon
An accurate, scalable and verifiable protocol for federated differentially private averaging. Mach. Learn. 111 (11) (2022)
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
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. NeurIPS (2022)
Mahsa Asadi, Aurélien Bellet, Odalric-Ambrym Maillard, Marc Tommasi
Collaborative Algorithms for Online Personalized Mean Estimation. Trans. Mach. Learn. Res. 2022 (2022)
Sina Sajadmanesh, Ali Shahin Shamsabadi, Aurélien Bellet, Daniel Gatica-Perez
GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation. CoRR (2022)
Aurélien Bellet, Anne-Marie Kermarrec, Erick Lavoie
D-Cliques: Compensating for Data Heterogeneity with Topology in Decentralized Federated Learning. SRDS (2022)
B. Le Bars, Aurélien Bellet, Marc Tommasi, Anne-Marie Kermarrec
Yes, Topology Matters in Decentralized Optimization: Refined Convergence and Topology Learning under Heterogeneous Data. CoRR (2022)
Gaurav Maheshwari, Pascal Denis, Mikaela Keller, Aurélien Bellet
Fair NLP Models with Differentially Private Text Encoders. CoRR (2022)
Yacine Belal, Aurélien Bellet, Sonia Ben Mokhtar, Vlad Nitu
PEPPER: Empowering User-Centric Recommender Systems over Gossip Learning. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6 (3) (2022)
Maxence Noble, Aurélien Bellet, Aymeric Dieuleveut
Differentially Private Federated Learning on Heterogeneous Data. AISTATS (2022)
Mahsa Asadi, Aurélien Bellet, Odalric-Ambrym Maillard, Marc Tommasi
Collaborative Algorithms for Online Personalized Mean Estimation. CoRR (2022)
Edwige Cyffers, Mathieu Even, Aurélien Bellet, Laurent Massoulié
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging. NeurIPS (2022)
Edwige Cyffers, Mathieu Even, Aurélien Bellet, Laurent Massoulié
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging. CoRR (2022)
Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent. CoRR (2022)
Yacine Belal, Aurélien Bellet, Sonia Ben Mokhtar, Vlad Nitu
PEPPER: Empowering User-Centric Recommender Systems over Gossip Learning. CoRR (2022)
Mohamed Maouche, Brij Mohan Lal Srivastava, Nathalie Vauquier, Aurélien Bellet, Marc Tommasi, Emmanuel Vincent
Enhancing Speech Privacy with Slicing. INTERSPEECH (2022)
Aurélien Bellet, Anne-Marie Kermarrec, Erick Lavoie
D-Cliques: Compensating NonIIDness in Decentralized Federated Learning with Topology. CoRR (2021)
Othmane Marfoq, Giovanni Neglia, Aurélien Bellet, Laetitia Kameni, Richard Vidal
Federated Multi-Task Learning under a Mixture of Distributions. NeurIPS (2021)
Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
Differentially Private Coordinate Descent for Composite Empirical Risk Minimization. CoRR (2021)
Maxence Noble, Aurélien Bellet, Aymeric Dieuleveut
Differentially Private Federated Learning on Heterogeneous Data. CoRR (2021)
Robin Vogel, Aurélien Bellet, Stéphan Clémençon
Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints. AISTATS (2021)
Othmane Marfoq, Giovanni Neglia, Aurélien Bellet, Laetitia Kameni, Richard Vidal
Federated Multi-Task Learning under a Mixture of Distributions. CoRR (2021)
Riad Ladjel, Nicolas Anciaux, Aurélien Bellet, Guillaume Scerri
Mitigating Leakage from Data Dependent Communications in Decentralized Computing using Differential Privacy. CoRR (2021)
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
Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 14 (1-2) (2021)
Brooks Paige, James Bell, Aurélien Bellet, Adrià Gascón, Daphne Ezer
Reconstructing Genotypes in Private Genomic Databases from Genetic Risk Scores. RECOMB (2020)
Valentina Zantedeschi, Aurélien Bellet, Marc Tommasi
Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs. AISTATS (2020)
William de Vazelhes, C. J. Carey, Yuan Tang, Nathalie Vauquier, Aurélien Bellet
metric-learn: Metric Learning Algorithms in Python. J. Mach. Learn. Res. 21 (2020)
James Bell, Aurélien Bellet, Adrià Gascón, Tejas Kulkarni
Private Protocols for U-Statistics in the Local Model and Beyond. AISTATS (2020)
César Sabater, Aurélien Bellet, Jan Ramon
Distributed Differentially Private Averaging with Improved Utility and Robustness to Malicious Parties. CoRR (2020)
Brij Mohan Lal Srivastava, Nathalie Vauquier, Md. Sahidullah, Aurélien Bellet, Marc Tommasi, Emmanuel Vincent
Evaluating Voice Conversion-Based Privacy Protection against Informed Attackers. ICASSP (2020)
Edwige Cyffers, Aurélien Bellet
Privacy Amplification by Decentralization. CoRR (2020)
Brij Mohan Lal Srivastava, Natalia A. Tomashenko, Xin Wang, Emmanuel Vincent, Junichi Yamagishi, Mohamed Maouche, Aurélien Bellet, Marc Tommasi
Design Choices for X-Vector Based Speaker Anonymization. INTERSPEECH (2020)
Robin Vogel, Aurélien Bellet, Stéphan Clémençon
Learning Fair Scoring Functions: Fairness Definitions, Algorithms and Generalization Bounds for Bipartite Ranking. CoRR (2020)
Mohamed Maouche, Brij Mohan Lal Srivastava, Nathalie Vauquier, Aurélien Bellet, Marc Tommasi, Emmanuel Vincent
A Comparative Study of Speech Anonymization Metrics. INTERSPEECH (2020)
Aurélien Bellet, Rachid Guerraoui, Hadrien Hendrikx
Who Started This Rumor? Quantifying the Natural Differential Privacy of Gossip Protocols. DISC (2020)
Brij Mohan Lal Srivastava, Natalia A. Tomashenko, Xin Wang, Emmanuel Vincent, Junichi Yamagishi, Mohamed Maouche, Aurélien Bellet, Marc Tommasi
Design Choices for X-vector Based Speaker Anonymization. CoRR (2020)
James Bell, Aurélien Bellet, Adrià Gascón, Tejas Kulkarni
Private Protocols for U-Statistics in the Local Model and Beyond. CoRR (2019)
William de Vazelhes, C. J. Carey, Yuan Tang, Nathalie Vauquier, Aurélien Bellet
metric-learn: Metric Learning Algorithms in Python. CoRR (2019)
Valentina Zantedeschi, Aurélien Bellet, Marc Tommasi
Communication-Efficient and Decentralized Multi-Task Boosting while Learning the Collaboration Graph. CoRR (2019)
Aurélien Bellet, Rachid Guerraoui, Hadrien Hendrikx
Who started this rumor? Quantifying the natural differential privacy guarantees of gossip protocols. CoRR (2019)
Robin Vogel, Aurélien Bellet, Stéphan Clémençon, Ons Jelassi, Guillaume Papa
Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning. CoRR (2019)
Brij Mohan Lal Srivastava, Aurélien Bellet, Marc Tommasi, Emmanuel Vincent
Privacy-Preserving Adversarial Representation Learning in ASR: Reality or Illusion? INTERSPEECH (2019)
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
Kernel Approximation Methods for Speech Recognition. J. Mach. Learn. Res. 20 (2019)
Robin Vogel, Aurélien Bellet, Stéphan Clémençon, Ons Jelassi, Guillaume Papa
Trade-Offs in Large-Scale Distributed Tuplewise Estimation And Learning. ECML/PKDD (2) (2019)
Brij Mohan Lal Srivastava, Nathalie Vauquier, Md. Sahidullah, Aurélien Bellet, Marc Tommasi, Emmanuel Vincent
Evaluating Voice Conversion-based Privacy Protection against Informed Attackers. CoRR (2019)
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, 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, Mariana Raykova, Hang Qi, Daniel Ramage, Ramesh Raskar, 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
Advances and Open Problems in Federated Learning. CoRR (2019)
Brij Mohan Lal Srivastava, Aurélien Bellet, Marc Tommasi, Emmanuel Vincent
Privacy-Preserving Adversarial Representation Learning in ASR: Reality or Illusion? CoRR (2019)
Kuan Liu, Aurélien Bellet
Escaping the curse of dimensionality in similarity learning: Efficient Frank-Wolfe algorithm and generalization bounds. Neurocomputing 333 (2019)
Robin Vogel, Aurélien Bellet, Stéphan Clémençon
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization. CoRR (2018)
Aurélien Bellet, Rachid Guerraoui, Mahsa Taziki, Marc Tommasi
Personalized and Private Peer-to-Peer Machine Learning. AISTATS (2018)
Robin Vogel, Aurélien Bellet, Stéphan Clémençon
A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization. ICML (2018)
Wenjie Zheng, Aurélien Bellet, Patrick Gallinari
A distributed Frank-Wolfe framework for learning low-rank matrices with the trace norm. Mach. Learn. 107 (8-10) (2018)
Melissa Ailem, Bowen Zhang, Aurélien Bellet, Pascal Denis, Fei Sha
A Probabilistic Model for Joint Learning of Word Embeddings from Texts and Images. EMNLP (2018)
Kuan Liu, Aurélien Bellet
Escaping the Curse of Dimensionality in Similarity Learning: Efficient Frank-Wolfe Algorithm and Generalization Bounds. CoRR (2018)
Pierre Dellenbach, Aurélien Bellet, Jan Ramon
Hiding in the Crowd: A Massively Distributed Algorithm for Private Averaging with Malicious Adversaries. CoRR (2018)
Wenjie Zheng, Aurélien Bellet, Patrick Gallinari
A Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm. CoRR (2017)
Paul Vanhaesebrouck, Aurélien Bellet, Marc Tommasi
Decentralized Collaborative Learning of Personalized Models over Networks. AISTATS (2017)
Avner May, Alireza Bagheri Garakani, Zhiyun Lu, Dong Guo, Kuan Liu, Aurélien Bellet, Linxi Fan, Michael Collins, Daniel J. Hsu, Brian Kingsbury, Michael Picheny, Fei Sha
Kernel Approximation Methods for Speech Recognition. CoRR (2017)
Aurélien Bellet, Rachid Guerraoui, Mahsa Taziki, Marc Tommasi
Fast and Differentially Private Algorithms for Decentralized Collaborative Machine Learning. CoRR (2017)
Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions. ICML (2016)
Guillaume Papa, Aurélien Bellet, Stéphan Clémençon
On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability. NIPS (2016)
Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions. CoRR (2016)
Paul Vanhaesebrouck, Aurélien Bellet, Marc Tommasi
Decentralized Collaborative Learning of Personalized Models over Networks. CoRR (2016)
Stéphan Clémençon, Igor Colin, Aurélien Bellet
Scaling-up Empirical Risk Minimization: Optimization of Incomplete $U$-statistics. J. Mach. Learn. Res. 17 (2016)
Aurélien Bellet, José Francisco Bernabeu, Amaury Habrard, Marc Sebban
Learning discriminative tree edit similarities for linear classification - Application to melody recognition. Neurocomputing 214 (2016)
Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha
A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition. CoRR (2016)
Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha
A comparison between deep neural nets and kernel acoustic models for speech recognition. ICASSP (2016)
Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
Extending Gossip Algorithms to Distributed Estimation of U-statistics. NIPS (2015)
Aurélien Bellet, Amaury Habrard
Robustness and generalization for metric learning. Neurocomputing 151 (2015)
Aurélien Bellet, Yingyu Liang, Alireza Bagheri Garakani, Maria-Florina Balcan, Fei Sha
A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning. SDM (2015)
Guillaume Papa, Stéphan Clémençon, Aurélien Bellet
SGD Algorithms based on Incomplete U-statistics: Large-Scale Minimization of Empirical Risk. NIPS (2015)
Kuan Liu, Aurélien Bellet, Fei Sha
Similarity Learning for High-Dimensional Sparse Data. AISTATS (2015)
Stéphan Clémençon, Aurélien Bellet, Igor Colin
Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics. CoRR (2015)
Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
Extending Gossip Algorithms to Distributed Estimation of U-Statistics. CoRR (2015)
Stéphan Clémençon, Aurélien Bellet, Ons Jelassi, Guillaume Papa
Scalability of Stochastic Gradient Descent based on "Smart" Sampling Techniques. INNS Conference on Big Data (2015)
Aurélien Bellet, Yingyu Liang, Alireza Bagheri Garakani, Maria-Florina Balcan, Fei Sha
Distributed Frank-Wolfe Algorithm: A Unified Framework for Communication-Efficient Sparse Learning. CoRR (2014)
Kuan Liu, Aurélien Bellet, Fei Sha
Similarity Learning for High-Dimensional Sparse Data. CoRR (2014)
Aurélien Bellet, Amaury Habrard, Emilie Morvant, Marc Sebban
Learning a priori constrained weighted majority votes. Mach. Learn. 97 (1-2) (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Aurélien Bellet