Rafael Pinot - RankMe

54 papers A* 12A 4B 1Journal 34Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Equalized Generative Treatment: Matching f-divergences for Fairness in Generative Models. CoRR Alexandre Verine, Rafael Pinot, Florian Le Bronnec
2025	J	`jnl`	ByzFL: Research Framework for Robust Federated Learning. CoRR Marc González, Rachid Guerraoui, Rafael Pinot, Geovani Rizk, John Stephan, François Taïani
2025	J	`jnl`	Fairness Meets Privacy: Integrating Differential Privacy and Demographic Parity in Multi-class Classification. CoRR Lilian Say, Christophe Denis, Rafael Pinot
2025	J	`jnl`	Robust Federated Inference. CoRR Akash Balasaheb Dhasade, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Maxime Jacovella, Anne-Marie Kermarrec, Rafael Pinot
2025	A	`conf`	Unveiling the Role of Randomization in Multiclass Adversarial Classification: Insights from Graph Theory. AISTATS Lucas Gnecco Heredia, Matteo Sammut, Muni Sreenivas Pydi, Rafael Pinot, Benjamin Négrevergne, Yann Chevaleyre
2025	J	`jnl`	Unveiling the Role of Randomization in Multiclass Adversarial Classification: Insights from Graph Theory. CoRR Lucas Gnecco Heredia, Matteo Sammut, Muni Sreenivas Pydi, Rafael Pinot, Benjamin Négrevergne, Yann Chevaleyre
2024	A*	`conf`	Brief Announcement: A Case for Byzantine Machine Learning. PODC Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
2024	J	`jnl`	Byzantine Machine Learning: A Primer. ACM Comput. Surv. Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
2024	A*	`conf`	Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates. ICML Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Geovani Rizk, Sasha Voitovych
2024	A*	`conf`	Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients. NeurIPS Youssef Allouah, Abdellah El Mrini, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
2024	J	`jnl`	Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients. CoRR Youssef Allouah, Abdellah El Mrini, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
2024	J	`jnl`	On the Relevance of Byzantine Robust Optimization Against Data Poisoning. CoRR Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
2024	J	`jnl`	Overcoming the Challenges of Batch Normalization in Federated Learning. CoRR Rachid Guerraoui, Rafael Pinot, Geovani Rizk, John Stephan, François Taïani
2024	J	`jnl`	PeerSwap: A Peer-Sampler with Randomness Guarantees. CoRR Rachid Guerraoui, Anne-Marie Kermarrec, Anastasiia Kucherenko, Rafael Pinot, Marijn de Vos
2024	B	`conf`	Peerswap: A Peer-Sampler with Randomness Guarantees. SRDS Rachid Guerraoui, Anne-Marie Kermarrec, Anastasiia Kucherenko, Rafael Pinot, Martijn de Vos
2024	A*	`conf`	Revisiting Ensembling in One-Shot Federated Learning. NeurIPS Youssef Allouah, Akash Balasaheb Dhasade, Rachid Guerraoui, Nirupam Gupta, Anne-Marie Kermarrec, Rafael Pinot, Rafael Pires, Rishi Sharma
2024	J	`jnl`	Revisiting Ensembling in One-Shot Federated Learning. CoRR Youssef Allouah, Akash Balasaheb Dhasade, Rachid Guerraoui, Nirupam Gupta, Anne-Marie Kermarrec, Rafael Pinot, Rafael Pires, Rishi Sharma
2024	—	`book`	Robust Machine Learning - Distributed Methods for Safe AI Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
2024	J	`jnl`	Tackling Byzantine Clients in Federated Learning. CoRR Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Geovani Rizk, Sasha Voitovych
2024	A	`conf`	Towards Practical Homomorphic Aggregation in Byzantine-Resilient Distributed Learning. Middleware Antoine Choffrut, Rachid Guerraoui, Rafael Pinot, Renaud Sirdey, John Stephan, Martin Zuber
2023	J	`jnl`	Distributed Learning with Curious and Adversarial Machines. CoRR Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
2023	A	`conf`	Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity. AISTATS Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
2023	J	`jnl`	Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity. CoRR Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
2023	J	`jnl`	On the Inherent Anonymity of Gossiping. CoRR Rachid Guerraoui, Anne-Marie Kermarrec, Anastasiia Kucherenko, Rafael Pinot, Sasha Voitovych
2023	A*	`conf`	On the Privacy-Robustness-Utility Trilemma in Distributed Learning. ICML Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
2023	J	`jnl`	Practical Homomorphic Aggregation for Byzantine ML. CoRR Antoine Choffrut, Rachid Guerraoui, Rafael Pinot, Renaud Sirdey, John Stephan, Martin Zuber
2023	A*	`conf`	Robust Collaborative Learning with Linear Gradient Overhead. ICML Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê-Nguyên Hoang, Rafael Pinot, John Stephan
2023	A*	`conf`	Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity. NeurIPS Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Geovani Rizk
2022	A*	`conf`	Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums. ICML Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
2022	J	`jnl`	Byzantine Machine Learning Made Easy by Resilient Averaging of Momentums. CoRR Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
2022	J	`jnl`	Making Byzantine Decentralized Learning Efficient. CoRR Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê Nguyên Hoang, Rafael Pinot, John Stephan
2022	J	`jnl`	On the Impossible Safety of Large AI Models. CoRR El-Mahdi El-Mhamdi, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê-Nguyên Hoang, Rafael Pinot, John Stephan
2022	J	`jnl`	On the robustness of randomized classifiers to adversarial examples. Mach. Learn. Rafael Pinot, Laurent Meunier, Florian Yger, Cédric Gouy-Pailler, Yann Chevaleyre, Jamal Atif
2022	A*	`conf`	Towards Consistency in Adversarial Classification. NeurIPS Laurent Meunier, Raphael Ettedgui, Rafael Pinot, Yann Chevaleyre, Jamal Atif
2022	J	`jnl`	Towards Consistency in Adversarial Classification. CoRR Laurent Meunier, Raphaël Ettedgui, Rafael Pinot, Yann Chevaleyre, Jamal Atif
2022	J	`jnl`	Towards Evading the Limits of Randomized Smoothing: A Theoretical Analysis. CoRR Raphael Ettedgui, Alexandre Araujo, Rafael Pinot, Yann Chevaleyre, Jamal Atif
2021	J	`jnl`	Combining Differential Privacy and Byzantine Resilience in Distributed SGD. CoRR Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Sébastien Rouault, John Stephan
2021	A*	`conf`	Mixed Nash Equilibria in the Adversarial Examples Game. ICML Laurent Meunier, Meyer Scetbon, Rafael Pinot, Jamal Atif, Yann Chevaleyre
2021	J	`jnl`	Mixed Nash Equilibria in the Adversarial Examples Game. CoRR Laurent Meunier, Meyer Scetbon, Rafael Pinot, Jamal Atif, Yann Chevaleyre
2021	J	`jnl`	On the robustness of randomized classifiers to adversarial examples. CoRR Rafael Pinot, Laurent Meunier, Florian Yger, Cédric Gouy-Pailler, Yann Chevaleyre, Jamal Atif
2021	J	`jnl`	SPEED: secure, PrivatE, and efficient deep learning. Mach. Learn. Arnaud Grivet Sébert, Rafael Pinot, Martin Zuber, Cédric Gouy-Pailler, Renaud Sirdey
2020	—	`conf`	Advocating for Multiple Defense Strategies Against Adversarial Examples. PKDD/ECML Workshops Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Négrevergne
2020	J	`jnl`	Advocating for Multiple Defense Strategies against Adversarial Examples. CoRR Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Négrevergne
2020	—	`—`	On the impact of randomization on robustness in machine learning. (Impact de la randomisation sur la robustesse des modèles d'apprentissage supervisé). Rafael Pinot
2020	A*	`conf`	Randomization matters How to defend against strong adversarial attacks. ICML Rafael Pinot, Raphael Ettedgui, Geovani Rizk, Yann Chevaleyre, Jamal Atif
2020	J	`jnl`	Randomization matters. How to defend against strong adversarial attacks. CoRR Rafael Pinot, Raphael Ettedgui, Geovani Rizk, Yann Chevaleyre, Jamal Atif
2020	J	`jnl`	SPEED: Secure, PrivatE, and Efficient Deep learning. CoRR Arnaud Grivet Sébert, Rafael Pinot, Martin Zuber, Cédric Gouy-Pailler, Renaud Sirdey
2019	J	`jnl`	A unified view on differential privacy and robustness to adversarial examples. CoRR Rafael Pinot, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
2019	J	`jnl`	Robust Neural Networks using Randomized Adversarial Training. CoRR Alexandre Araujo, Rafael Pinot, Benjamin Négrevergne, Laurent Meunier, Yann Chevaleyre, Florian Yger, Jamal Atif
2019	A*	`conf`	Theoretical evidence for adversarial robustness through randomization. NeurIPS Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
2019	J	`jnl`	Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family. CoRR Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
2018	A	`conf`	Graph-based Clustering under Differential Privacy. UAI Rafael Pinot, Anne Morvan, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
2018	J	`jnl`	Graph-based Clustering under Differential Privacy. CoRR Rafael Pinot, Anne Morvan, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
2018	J	`jnl`	Minimum spanning tree release under differential privacy constraints. CoRR Rafael Pinot