Aurélien Bellet

147 papers A* 22A 18B 3Misc 2Journal 92Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adaptive Personalized Federated Learning via Multi-task Averaging of Kernel Mean Embeddings. CoRR Jean-Baptiste Fermanian, Batiste Le Bars, Aurélien Bellet
2026	J	`jnl`	Loss Gap Parity for Fairness in Heterogeneous Federated Learning. CoRR Brahim Erraji, Michaël Perrot, Aurélien Bellet
2026	J	`jnl`	Membership Inference Attacks from Causal Principles. CoRR Mathieu Even, Clément Berenfeld, Linus Bleistein, Tudor Cebere, Julie Josse, Aurélien Bellet
2026	J	`jnl`	On Gossip Algorithms for Machine Learning with Pairwise Objectives. CoRR Igor Colin, Aurélien Bellet, Stéphan Clémençon, Joseph Salmon
2026	J	`jnl`	On Gossip Algorithms for Machine Learning with Pairwise Objectives. Trans. Mach. Learn. Res. Igor Colin, Aurélien Bellet, Stéphan Clémençon, Joseph Salmon
2026	J	`jnl`	Optimal Transport under Group Fairness Constraints. CoRR Linus Bleistein, Mathieu Dagréou, Francisco Andrade, Thomas Boudou, Aurélien Bellet
2026	J	`jnl`	Principled Federated Random Forests for Heterogeneous Data. CoRR Rémi Khellaf, Erwan Scornet, Aurélien Bellet, Julie Josse
2026	J	`jnl`	Privacy Amplification Persists under Unlimited Synthetic Data Release. CoRR Clément Pierquin, Aurélien Bellet, Marc Tommasi, Matthieu Boussard
2026	J	`jnl`	Privacy in Theory, Bugs in Practice: Grey-Box Auditing of Differential Privacy Libraries. CoRR Tudor Cebere, David Evans, Damien Desfontaines, Aurélien Bellet, Jack Fitzsimons
2025	J	`jnl`	Differentially Private and Federated Structure Learning in Bayesian Networks. CoRR Ghita Fassy El Fehri, Aurélien Bellet, Philippe Bastien
2025	J	`jnl`	Federated Causal Inference from Multi-Site Observational Data via Propensity Score Aggregation. CoRR Rémi Khellaf, Aurélien Bellet, Julie Josse
2025	A	`conf`	Federated Causal Inference: Multi-Study ATE Estimation beyond Meta-Analysis. AISTATS Rémi Khellaf, Aurélien Bellet, Julie Josse
2025	J	`jnl`	Federated Learning for MRI-based BrainAGE: a multicenter study on post-stroke functional outcome prediction. CoRR Vincent Roca, Marc Tommasi, Paul Andrey, Aurélien Bellet, Markus D. Schirmer, Hilde Henon, Laurent Puy, Julien Ramon, Grégory Kuchcinski, Martin Bretzner, Renaud Lopes
2025	J	`jnl`	Generalization under Byzantine & Poisoning Attacks: Tight Stability Bounds in Robust Distributed Learning. CoRR Thomas Boudou, Batiste Le Bars, Nirupam Gupta, Aurélien Bellet
2025	J	`jnl`	Model Agnostic Differentially Private Causal Inference. CoRR Christian Janos Lebeda, Mathieu Even, Aurélien Bellet, Julie Josse
2025	J	`jnl`	Optimal Transport with Heterogeneously Missing Data. CoRR Linus Bleistein, Aurélien Bellet, Julie Josse
2025	A*	`conf`	Privacy Amplification Through Synthetic Data: Insights from Linear Regression. ICML Clément Pierquin, Aurélien Bellet, Marc Tommasi, Matthieu Boussard
2025	J	`jnl`	Privacy Amplification Through Synthetic Data: Insights from Linear Regression. CoRR Clément Pierquin, Aurélien Bellet, Marc Tommasi, Matthieu Boussard
2025	J	`jnl`	Private Rate-Constrained Optimization with Applications to Fair Learning. CoRR Mohammad Yaghini, Tudor Cebere, Michael Menart, Aurélien Bellet, Nicolas Papernot
2025	A*	`conf`	Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model. ICLR Tudor Ioan Cebere, Aurélien Bellet, Nicolas Papernot
2025	J	`jnl`	Unified Privacy Guarantees for Decentralized Learning via Matrix Factorization. CoRR Aurélien Bellet, Edwige Cyffers, Davide Frey, Romaric Gaudel, Dimitri Lerévérend, François Taïani
2024	A*	`conf`	Confidential-DPproof: Confidential Proof of Differentially Private Training. ICLR Ali Shahin Shamsabadi, Gefei Tan, Tudor Cebere, Aurélien Bellet, Hamed Haddadi, Nicolas Papernot, Xiao Wang, Adrian Weller
2024	A*	`conf`	DP-SGD Without Clipping: The Lipschitz Neural Network Way. ICLR Louis Béthune, Thomas Massena, Thibaut Boissin, Aurélien Bellet, Franck Mamalet, Yannick Prudent, Corentin Friedrich, Mathieu Serrurier, David Vigouroux
2024	A*	`conf`	Differentially Private Decentralized Learning with Random Walks. ICML Edwige Cyffers, Aurélien Bellet, Jalaj Upadhyay
2024	J	`jnl`	Differentially Private Decentralized Learning with Random Walks. CoRR Edwige Cyffers, Aurélien Bellet, Jalaj Upadhyay
2024	J	`jnl`	Federated Causal Inference: Multi-Centric ATE Estimation beyond Meta-Analysis. CoRR Rémi Khellaf, Aurélien Bellet, Julie Josse
2024	A*	`conf`	Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm. ICML Batiste Le Bars, Aurélien Bellet, Marc Tommasi, Kevin Scaman, Giovanni Neglia
2024	J	`jnl`	Nebula: Efficient, Private and Accurate Histogram Estimation. CoRR Ali Shahin Shamsabadi, Peter Snyder, Ralph Giles, Aurélien Bellet, Hamed Haddadi
2024	A*	`conf`	Privacy Attacks in Decentralized Learning. ICML Abdellah El Mrini, Edwige Cyffers, Aurélien Bellet
2024	J	`jnl`	Privacy Attacks in Decentralized Learning. CoRR Abdellah El Mrini, Edwige Cyffers, Aurélien Bellet
2024	A*	`conf`	Rényi Pufferfish Privacy: General Additive Noise Mechanisms and Privacy Amplification by Iteration via Shift Reduction Lemmas. ICML Clément Pierquin, Aurélien Bellet, Marc Tommasi, Matthieu Boussard
2024	J	`jnl`	Synthetic Data Generation for Intersectional Fairness by Leveraging Hierarchical Group Structure. CoRR Gaurav Maheshwari, Aurélien Bellet, Pascal Denis, Mikaela Keller
2024	A	`conf`	The Relative Gaussian Mechanism and its Application to Private Gradient Descent. AISTATS Hadrien Hendrikx, Paul Mangold, Aurélien Bellet
2024	J	`jnl`	Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model. CoRR Tudor Cebere, Aurélien Bellet, Nicolas Papernot
2023	J	`jnl`	DP-SGD Without Clipping: The Lipschitz Neural Network Way. CoRR Louis Béthune, Thomas Massena, Thibaut Boissin, Yannick Prudent, Corentin Friedrich, Franck Mamalet, Aurélien Bellet, Mathieu Serrurier, David Vigouroux
2023	A*	`conf`	Differential Privacy has Bounded Impact on Fairness in Classification. ICML Paul Mangold, Michaël Perrot, Aurélien Bellet, Marc Tommasi
2023	J	`jnl`	Differentially Private Speaker Anonymization. Proc. Priv. Enhancing Technol. Ali Shahin Shamsabadi, Brij Mohan Lal Srivastava, Aurélien Bellet, Nathalie Vauquier, Emmanuel Vincent, Mohamed Maouche, Marc Tommasi, Nicolas Papernot
2023	A*	`conf`	Fair Without Leveling Down: A New Intersectional Fairness Definition. EMNLP Gaurav Maheshwari, Aurélien Bellet, Pascal Denis, Mikaela Keller
2023	A*	`conf`	From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning. ICML Edwige Cyffers, Aurélien Bellet, Debabrota Basu
2023	J	`jnl`	From Noisy Fixed-Point Iterations to Private ADMM for Centralized and Federated Learning. CoRR Edwige Cyffers, Aurélien Bellet, Debabrota Basu
2023	A*	`conf`	GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation. USENIX Security Symposium Sina Sajadmanesh, Ali Shahin Shamsabadi, Aurélien Bellet, Daniel Gatica-Perez
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`	How to Capture Intersectional Fairness. CoRR Gaurav Maheshwari, Aurélien Bellet, Pascal Denis, Mikaela Keller
2023	J	`jnl`	Improved Stability and Generalization Analysis of the Decentralized SGD Algorithm. CoRR Batiste Le Bars, Aurélien Bellet, Marc Tommasi
2023	A*	`conf`	One-Shot Federated Conformal Prediction. ICML Pierre Humbert, Batiste Le Bars, Aurélien Bellet, Sylvain Arlot
2023	A	`conf`	Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data. AISTATS Batiste Le Bars, Aurélien Bellet, Marc Tommasi, Erick Lavoie, Anne-Marie Kermarrec
2023	J	`jnl`	Rényi Pufferfish Privacy: General Additive Noise Mechanisms and Privacy Amplification by Iteration. CoRR Clément Pierquin, Aurélien Bellet, Marc Tommasi, Matthieu Boussard
2023	J	`jnl`	The Relative Gaussian Mechanism and its Application to Private Gradient Descent. CoRR Hadrien Hendrikx, Paul Mangold, Aurélien Bellet
2022	J	`jnl`	An accurate, scalable and verifiable protocol for federated differentially private averaging. Mach. Learn. César Sabater, Aurélien Bellet, Jan Ramon
2022	J	`jnl`	Collaborative Algorithms for Online Personalized Mean Estimation. CoRR Mahsa Asadi, Aurélien Bellet, Odalric-Ambrym Maillard, Marc Tommasi
2022	J	`jnl`	Collaborative Algorithms for Online Personalized Mean Estimation. Trans. Mach. Learn. Res. Mahsa Asadi, Aurélien Bellet, Odalric-Ambrym Maillard, Marc Tommasi
2022	B	`conf`	D-Cliques: Compensating for Data Heterogeneity with Topology in Decentralized Federated Learning. SRDS Aurélien Bellet, Anne-Marie Kermarrec, Erick Lavoie
2022	A*	`conf`	Differentially Private Coordinate Descent for Composite Empirical Risk Minimization. ICML Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
2022	A	`conf`	Differentially Private Federated Learning on Heterogeneous Data. AISTATS Maxence Noble, Aurélien Bellet, Aymeric Dieuleveut
2022	J	`jnl`	Differentially Private Speaker Anonymization. CoRR Ali Shahin Shamsabadi, Brij Mohan Lal Srivastava, Aurélien Bellet, Nathalie Vauquier, Emmanuel Vincent, Mohamed Maouche, Marc Tommasi, Nicolas Papernot
2022	A	`conf`	Enhancing Speech Privacy with Slicing. INTERSPEECH Mohamed Maouche, Brij Mohan Lal Srivastava, Nathalie Vauquier, Aurélien Bellet, Marc Tommasi, Emmanuel Vincent
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	—	`conf`	Fair NLP Models with Differentially Private Text Encoders. EMNLP (Findings) Gaurav Maheshwari, Pascal Denis, Mikaela Keller, Aurélien Bellet
2022	J	`jnl`	Fair NLP Models with Differentially Private Text Encoders. CoRR Gaurav Maheshwari, Pascal Denis, Mikaela Keller, Aurélien Bellet
2022	J	`jnl`	Fairness Certificates for Differentially Private Classification. CoRR Paul Mangold, Michaël Perrot, Aurélien Bellet, Marc Tommasi
2022	J	`jnl`	GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation. CoRR Sina Sajadmanesh, Ali Shahin Shamsabadi, Aurélien Bellet, Daniel Gatica-Perez
2022	J	`jnl`	High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent. CoRR Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
2022	A*	`conf`	Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging. NeurIPS Edwige Cyffers, Mathieu Even, Aurélien Bellet, Laurent Massoulié
2022	J	`jnl`	Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging. CoRR Edwige Cyffers, Mathieu Even, Aurélien Bellet, Laurent Massoulié
2022	J	`jnl`	PEPPER: Empowering User-Centric Recommender Systems over Gossip Learning. CoRR Yacine Belal, Aurélien Bellet, Sonia Ben Mokhtar, Vlad Nitu
2022	J	`jnl`	PEPPER: Empowering User-Centric Recommender Systems over Gossip Learning. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. Yacine Belal, Aurélien Bellet, Sonia Ben Mokhtar, Vlad Nitu
2022	A	`conf`	Privacy Amplification by Decentralization. AISTATS Edwige Cyffers, Aurélien Bellet
2022	J	`jnl`	Privacy and Utility of X-Vector Based Speaker Anonymization. IEEE ACM Trans. Audio Speech Lang. Process. Brij Mohan Lal Srivastava, Mohamed Maouche, Md. Sahidullah, Emmanuel Vincent, Aurélien Bellet, Marc Tommasi, Natalia A. Tomashenko, Xin Wang, Junichi Yamagishi
2022	J	`jnl`	Yes, Topology Matters in Decentralized Optimization: Refined Convergence and Topology Learning under Heterogeneous Data. CoRR Batiste Le Bars, Aurélien Bellet, Marc Tommasi, Anne-Marie Kermarrec
2021	J	`jnl`	Advances and Open Problems in Federated Learning. Found. Trends Mach. Learn. 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
2021	—	`book`	Contributions to Decentralized and Privacy-Preserving Machine Learning. Aurélien Bellet
2021	J	`jnl`	D-Cliques: Compensating NonIIDness in Decentralized Federated Learning with Topology. CoRR Aurélien Bellet, Anne-Marie Kermarrec, Erick Lavoie
2021	J	`jnl`	Differentially Private Coordinate Descent for Composite Empirical Risk Minimization. CoRR Paul Mangold, Aurélien Bellet, Joseph Salmon, Marc Tommasi
2021	J	`jnl`	Differentially Private Federated Learning on Heterogeneous Data. CoRR Maxence Noble, Aurélien Bellet, Aymeric Dieuleveut
2021	A*	`conf`	Federated Multi-Task Learning under a Mixture of Distributions. NeurIPS Othmane Marfoq, Giovanni Neglia, Aurélien Bellet, Laetitia Kameni, Richard Vidal
2021	J	`jnl`	Federated Multi-Task Learning under a Mixture of Distributions. CoRR Othmane Marfoq, Giovanni Neglia, Aurélien Bellet, Laetitia Kameni, Richard Vidal
2021	A	`conf`	Learning Fair Scoring Functions: Bipartite Ranking under ROC-based Fairness Constraints. AISTATS Robin Vogel, Aurélien Bellet, Stéphan Clémençon
2021	J	`jnl`	Mitigating Leakage from Data Dependent Communications in Decentralized Computing using Differential Privacy. CoRR Riad Ladjel, Nicolas Anciaux, Aurélien Bellet, Guillaume Scerri
2021	J	`jnl`	Reconstructing Genotypes in Private Genomic Databases from Genetic Risk Scores. J. Comput. Biol. Brooks Paige, James Bell, Aurélien Bellet, Adrià Gascón, Daphne Ezer
2020	A	`conf`	A Comparative Study of Speech Anonymization Metrics. INTERSPEECH Mohamed Maouche, Brij Mohan Lal Srivastava, Nathalie Vauquier, Aurélien Bellet, Marc Tommasi, Emmanuel Vincent
2020	A	`conf`	Design Choices for X-Vector Based Speaker Anonymization. INTERSPEECH Brij Mohan Lal Srivastava, Natalia A. Tomashenko, Xin Wang, Emmanuel Vincent, Junichi Yamagishi, Mohamed Maouche, Aurélien Bellet, Marc Tommasi
2020	J	`jnl`	Design Choices for X-vector Based Speaker Anonymization. CoRR Brij Mohan Lal Srivastava, Natalia A. Tomashenko, Xin Wang, Emmanuel Vincent, Junichi Yamagishi, Mohamed Maouche, Aurélien Bellet, Marc Tommasi
2020	J	`jnl`	Distributed Differentially Private Averaging with Improved Utility and Robustness to Malicious Parties. CoRR César Sabater, Aurélien Bellet, Jan Ramon
2020	Misc	`conf`	Evaluating Voice Conversion-Based Privacy Protection against Informed Attackers. ICASSP Brij Mohan Lal Srivastava, Nathalie Vauquier, Md. Sahidullah, Aurélien Bellet, Marc Tommasi, Emmanuel Vincent
2020	A	`conf`	Fully Decentralized Joint Learning of Personalized Models and Collaboration Graphs. AISTATS Valentina Zantedeschi, Aurélien Bellet, Marc Tommasi
2020	J	`jnl`	Learning Fair Scoring Functions: Fairness Definitions, Algorithms and Generalization Bounds for Bipartite Ranking. CoRR Robin Vogel, Aurélien Bellet, Stéphan Clémençon
2020	J	`jnl`	Privacy Amplification by Decentralization. CoRR Edwige Cyffers, Aurélien Bellet
2020	A	`conf`	Private Protocols for U-Statistics in the Local Model and Beyond. AISTATS James Bell, Aurélien Bellet, Adrià Gascón, Tejas Kulkarni
2020	B	`conf`	Reconstructing Genotypes in Private Genomic Databases from Genetic Risk Scores. RECOMB Brooks Paige, James Bell, Aurélien Bellet, Adrià Gascón, Daphne Ezer
2020	A	`conf`	Who Started This Rumor? Quantifying the Natural Differential Privacy of Gossip Protocols. DISC Aurélien Bellet, Rachid Guerraoui, Hadrien Hendrikx
2020	J	`jnl`	metric-learn: Metric Learning Algorithms in Python. J. Mach. Learn. Res. William de Vazelhes, CJ Carey, Yuan Tang, Nathalie Vauquier, Aurélien Bellet
2019	J	`jnl`	Advances and Open Problems in Federated Learning. CoRR 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
2019	J	`jnl`	Communication-Efficient and Decentralized Multi-Task Boosting while Learning the Collaboration Graph. CoRR Valentina Zantedeschi, Aurélien Bellet, Marc Tommasi
2019	J	`jnl`	Escaping the curse of dimensionality in similarity learning: Efficient Frank-Wolfe algorithm and generalization bounds. Neurocomputing Kuan Liu, Aurélien Bellet
2019	J	`jnl`	Evaluating Voice Conversion-based Privacy Protection against Informed Attackers. CoRR Brij Mohan Lal Srivastava, Nathalie Vauquier, Md. Sahidullah, Aurélien Bellet, Marc Tommasi, Emmanuel Vincent
2019	J	`jnl`	Kernel Approximation Methods for Speech Recognition. J. Mach. Learn. Res. 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
2019	A	`conf`	Privacy-Preserving Adversarial Representation Learning in ASR: Reality or Illusion? INTERSPEECH Brij Mohan Lal Srivastava, Aurélien Bellet, Marc Tommasi, Emmanuel Vincent
2019	J	`jnl`	Privacy-Preserving Adversarial Representation Learning in ASR: Reality or Illusion? CoRR Brij Mohan Lal Srivastava, Aurélien Bellet, Marc Tommasi, Emmanuel Vincent
2019	J	`jnl`	Private Protocols for U-Statistics in the Local Model and Beyond. CoRR James Bell, Aurélien Bellet, Adrià Gascón, Tejas Kulkarni
2019	—	`conf`	Trade-Offs in Large-Scale Distributed Tuplewise Estimation And Learning. ECML/PKDD (2) Robin Vogel, Aurélien Bellet, Stéphan Clémençon, Ons Jelassi, Guillaume Papa
2019	J	`jnl`	Trade-offs in Large-Scale Distributed Tuplewise Estimation and Learning. CoRR Robin Vogel, Aurélien Bellet, Stéphan Clémençon, Ons Jelassi, Guillaume Papa
2019	J	`jnl`	Who started this rumor? Quantifying the natural differential privacy guarantees of gossip protocols. CoRR Aurélien Bellet, Rachid Guerraoui, Hadrien Hendrikx
2019	J	`jnl`	metric-learn: Metric Learning Algorithms in Python. CoRR William de Vazelhes, CJ Carey, Yuan Tang, Nathalie Vauquier, Aurélien Bellet
2018	A*	`conf`	A Probabilistic Model for Joint Learning of Word Embeddings from Texts and Images. EMNLP Melissa Ailem, Bowen Zhang, Aurélien Bellet, Pascal Denis, Fei Sha
2018	A*	`conf`	A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization. ICML Robin Vogel, Aurélien Bellet, Stéphan Clémençon
2018	J	`jnl`	A Probabilistic Theory of Supervised Similarity Learning for Pointwise ROC Curve Optimization. CoRR Robin Vogel, Aurélien Bellet, Stéphan Clémençon
2018	J	`jnl`	A distributed Frank-Wolfe framework for learning low-rank matrices with the trace norm. Mach. Learn. Wenjie Zheng, Aurélien Bellet, Patrick Gallinari
2018	J	`jnl`	Escaping the Curse of Dimensionality in Similarity Learning: Efficient Frank-Wolfe Algorithm and Generalization Bounds. CoRR Kuan Liu, Aurélien Bellet
2018	J	`jnl`	Hiding in the Crowd: A Massively Distributed Algorithm for Private Averaging with Malicious Adversaries. CoRR Pierre Dellenbach, Aurélien Bellet, Jan Ramon
2018	A	`conf`	Personalized and Private Peer-to-Peer Machine Learning. AISTATS Aurélien Bellet, Rachid Guerraoui, Mahsa Taziki, Marc Tommasi
2017	J	`jnl`	A Distributed Frank-Wolfe Framework for Learning Low-Rank Matrices with the Trace Norm. CoRR Wenjie Zheng, Aurélien Bellet, Patrick Gallinari
2017	A	`conf`	Decentralized Collaborative Learning of Personalized Models over Networks. AISTATS Paul Vanhaesebrouck, Aurélien Bellet, Marc Tommasi
2017	J	`jnl`	Fast and Differentially Private Algorithms for Decentralized Collaborative Machine Learning. CoRR Aurélien Bellet, Rachid Guerraoui, Mahsa Taziki, Marc Tommasi
2017	J	`jnl`	Kernel Approximation Methods for Speech Recognition. CoRR 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
2016	J	`jnl`	A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition. CoRR Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha
2016	Misc	`conf`	A comparison between deep neural nets and kernel acoustic models for speech recognition. ICASSP Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha
2016	J	`jnl`	Decentralized Collaborative Learning of Personalized Models over Networks. CoRR Paul Vanhaesebrouck, Aurélien Bellet, Marc Tommasi
2016	A*	`conf`	Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions. ICML Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
2016	J	`jnl`	Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions. CoRR Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
2016	J	`jnl`	Learning discriminative tree edit similarities for linear classification - Application to melody recognition. Neurocomputing Aurélien Bellet, José Francisco Bernabeu, Amaury Habrard, Marc Sebban
2016	—	`conf`	On Graph Reconstruction via Empirical Risk Minimization: Fast Learning Rates and Scalability. NIPS Guillaume Papa, Aurélien Bellet, Stéphan Clémençon
2016	J	`jnl`	Scaling-up Empirical Risk Minimization: Optimization of Incomplete $U$-statistics. J. Mach. Learn. Res. Stéphan Clémençon, Igor Colin, Aurélien Bellet
2015	A	`conf`	A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning. SDM Aurélien Bellet, Yingyu Liang, Alireza Bagheri Garakani, Maria-Florina Balcan, Fei Sha
2015	J	`jnl`	Extending Gossip Algorithms to Distributed Estimation of U-Statistics. CoRR Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
2015	—	`conf`	Extending Gossip Algorithms to Distributed Estimation of U-statistics. NIPS Igor Colin, Aurélien Bellet, Joseph Salmon, Stéphan Clémençon
2015	—	`book`	Metric Learning Aurélien Bellet, Amaury Habrard, Marc Sebban
2015	J	`jnl`	Robustness and generalization for metric learning. Neurocomputing Aurélien Bellet, Amaury Habrard
2015	—	`conf`	SGD Algorithms based on Incomplete U-statistics: Large-Scale Minimization of Empirical Risk. NIPS Guillaume Papa, Stéphan Clémençon, Aurélien Bellet
2015	—	`conf`	Scalability of Stochastic Gradient Descent based on "Smart" Sampling Techniques. INNS Conference on Big Data Stéphan Clémençon, Aurélien Bellet, Ons Jelassi, Guillaume Papa
2015	J	`jnl`	Scaling-up Empirical Risk Minimization: Optimization of Incomplete U-statistics. CoRR Stéphan Clémençon, Aurélien Bellet, Igor Colin
2015	A	`conf`	Similarity Learning for High-Dimensional Sparse Data. AISTATS Kuan Liu, Aurélien Bellet, Fei Sha
2014	J	`jnl`	Distributed Frank-Wolfe Algorithm: A Unified Framework for Communication-Efficient Sparse Learning. CoRR Aurélien Bellet, Yingyu Liang, Alireza Bagheri Garakani, Maria-Florina Balcan, Fei Sha
2014	J	`jnl`	How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets. CoRR Zhiyun Lu, Avner May, Kuan Liu, Alireza Bagheri Garakani, Dong Guo, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha
2014	J	`jnl`	Learning a priori constrained weighted majority votes. Mach. Learn. Aurélien Bellet, Amaury Habrard, Emilie Morvant, Marc Sebban
2014	J	`jnl`	Similarity Learning for High-Dimensional Sparse Data. CoRR Kuan Liu, Aurélien Bellet, Fei Sha
2014	A*	`conf`	Sparse Compositional Metric Learning. AAAI Yuan Shi, Aurélien Bellet, Fei Sha
2014	J	`jnl`	Sparse Compositional Metric Learning. CoRR Yuan Shi, Aurélien Bellet, Fei Sha
2013	J	`jnl`	A Survey on Metric Learning for Feature Vectors and Structured Data. CoRR Aurélien Bellet, Amaury Habrard, Marc Sebban
2013	J	`jnl`	Supervised Metric Learning with Generalization Guarantees. CoRR Aurélien Bellet
2012	J	`jnl`	Good edit similarity learning by loss minimization. Mach. Learn. Aurélien Bellet, Amaury Habrard, Marc Sebban
2012	J	`jnl`	Robustness and Generalization for Metric Learning CoRR Aurélien Bellet, Amaury Habrard
2012	A*	`conf`	Similarity Learning for Provably Accurate Sparse Linear Classification. ICML Aurélien Bellet, Amaury Habrard, Marc Sebban
2012	—	`—`	Supervised metric learning with generalization guarantees. (Apprentissage supervisé de métriques avec garanties en généralisation). Aurélien Bellet
2011	B	`conf`	An Experimental Study on Learning with Good Edit Similarity Functions. ICTAI Aurélien Bellet, Marc Sebban, Amaury Habrard
2011	—	`conf`	Learning Good Edit Similarities with Generalization Guarantees. ECML/PKDD (1) Aurélien Bellet, Amaury Habrard, Marc Sebban
2010	J	`jnl`	Learning state machine-based string edit kernels. Pattern Recognit. Aurélien Bellet, Marc Bernard, Thierry Murgue, Marc Sebban