Rafael Pinot

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 38

Top Topics

Distributed Learning

Manually Labeled Training Data

Differential Privacy

Top Venues

Publications

Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
Byzantine Machine Learning: A Primer. ACM Comput. Surv. 56 (7) (2024)
Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
Brief Announcement: A Case for Byzantine Machine Learning. PODC (2024)
Rachid Guerraoui, Rafael Pinot, Geovani Rizk, John Stephan, François Taïani
Overcoming the Challenges of Batch Normalization in Federated Learning. CoRR (2024)
Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Geovani Rizk, Sasha Voitovych
Tackling Byzantine Clients in Federated Learning. CoRR (2024)
Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot
On the Relevance of Byzantine Robust Optimization Against Data Poisoning. CoRR (2024)
Rachid Guerraoui, Anne-Marie Kermarrec, Anastasiia Kucherenko, Rafael Pinot, Sasha Voitovych
On the Inherent Anonymity of Gossiping. CoRR (2023)
Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity. AISTATS (2023)
Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Geovani Rizk
Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity. NeurIPS (2023)
Youssef Allouah, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity. CoRR (2023)
Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
On the Privacy-Robustness-Utility Trilemma in Distributed Learning. ICML (2023)
Antoine Choffrut, Rachid Guerraoui, Rafael Pinot, Renaud Sirdey, John Stephan, Martin Zuber
Practical Homomorphic Aggregation for Byzantine ML. CoRR (2023)
Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê-Nguyên Hoang, Rafael Pinot, John Stephan
Robust Collaborative Learning with Linear Gradient Overhead. ICML (2023)
Youssef Allouah, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
Distributed Learning with Curious and Adversarial Machines. CoRR (2023)
Laurent Meunier, Raphaël Ettedgui, Rafael Pinot, Yann Chevaleyre, Jamal Atif
Towards Consistency in Adversarial Classification. CoRR (2022)
El-Mahdi El-Mhamdi, Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê-Nguyên Hoang, Rafael Pinot, John Stephan
SoK: On the Impossible Security of Very Large Foundation Models. CoRR (2022)
Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Lê Nguyên Hoang, Rafael Pinot, John Stephan
Making Byzantine Decentralized Learning Efficient. CoRR (2022)
Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums. ICML (2022)
Rafael Pinot, Laurent Meunier, Florian Yger, Cédric Gouy-Pailler, Yann Chevaleyre, Jamal Atif
On the robustness of randomized classifiers to adversarial examples. Mach. Learn. 111 (9) (2022)
Sadegh Farhadkhani, Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, John Stephan
Byzantine Machine Learning Made Easy by Resilient Averaging of Momentums. CoRR (2022)
Raphael Ettedgui, Alexandre Araujo, Rafael Pinot, Yann Chevaleyre, Jamal Atif
Towards Evading the Limits of Randomized Smoothing: A Theoretical Analysis. CoRR (2022)
Laurent Meunier, Raphael Ettedgui, Rafael Pinot, Yann Chevaleyre, Jamal Atif
Towards Consistency in Adversarial Classification. NeurIPS (2022)
Laurent Meunier, Meyer Scetbon, Rafael Pinot, Jamal Atif, Yann Chevaleyre
Mixed Nash Equilibria in the Adversarial Examples Game. CoRR (2021)
Arnaud Grivet Sébert, Rafael Pinot, Martin Zuber, Cédric Gouy-Pailler, Renaud Sirdey
SPEED: secure, PrivatE, and efficient deep learning. Mach. Learn. 110 (4) (2021)
Laurent Meunier, Meyer Scetbon, Rafael Pinot, Jamal Atif, Yann Chevaleyre
Mixed Nash Equilibria in the Adversarial Examples Game. ICML (2021)
Rachid Guerraoui, Nirupam Gupta, Rafael Pinot, Sebastien Rouault, John Stephan
Combining Differential Privacy and Byzantine Resilience in Distributed SGD. CoRR (2021)
Rafael Pinot, Laurent Meunier, Florian Yger, Cédric Gouy-Pailler, Yann Chevaleyre, Jamal Atif
On the robustness of randomized classifiers to adversarial examples. CoRR (2021)
Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Négrevergne
Advocating for Multiple Defense Strategies Against Adversarial Examples. PKDD/ECML Workshops (2020)
Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Négrevergne
Advocating for Multiple Defense Strategies against Adversarial Examples. CoRR (2020)
Rafael Pinot, Raphael Ettedgui, Geovani Rizk, Yann Chevaleyre, Jamal Atif
Randomization matters. How to defend against strong adversarial attacks. CoRR (2020)
Rafael Pinot, Raphael Ettedgui, Geovani Rizk, Yann Chevaleyre, Jamal Atif
Randomization matters How to defend against strong adversarial attacks. ICML (2020)
Arnaud Grivet Sébert, Rafael Pinot, Martin Zuber, Cédric Gouy-Pailler, Renaud Sirdey
SPEED: Secure, PrivatE, and Efficient Deep learning. CoRR (2020)
Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family. CoRR (2019)
Rafael Pinot, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
A unified view on differential privacy and robustness to adversarial examples. CoRR (2019)
Alexandre Araujo, Rafael Pinot, Benjamin Négrevergne, Laurent Meunier, Yann Chevaleyre, Florian Yger, Jamal Atif
Robust Neural Networks using Randomized Adversarial Training. CoRR (2019)
Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
Theoretical evidence for adversarial robustness through randomization. NeurIPS (2019)
Rafael Pinot
Minimum spanning tree release under differential privacy constraints. CoRR (2018)
Rafael Pinot, Anne Morvan, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
Graph-based Clustering under Differential Privacy. UAI (2018)
Rafael Pinot, Anne Morvan, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
Graph-based Clustering under Differential Privacy. CoRR (2018)