Rafael Pinot
13 papers · 2019–2026 · 4 venues · across top CS/AI venues
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Achievements
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(2)
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Keyword Pioneer
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Century Club Β· Bronze
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Keyword Collector
(55)
Venues
Top co-authors
Research topics
Machine Learning
(12)
Learning Types Β· Machine Learning
(8)
Optimization & Theory
(7)
Artificial Intelligence
(5)
Core AI
(4)
Mathematics & Optimization
(3)
Learning Paradigms Β· Machine Learning
(3)
Application Areas
(2)
Learning Paradigms Β· Artificial Intelligence
(2)
Optimization
(2)
Deep Learning
(1)
Security & Privacy
(1)
Core Methods
(1)
Differential Privacy
(1)
Learning Types Β· Deep Learning
(1)
Keywords
distributed learning
(6)
adversarial robustness
(4)
byzantine resilience
(3)
data heterogeneity
(3)
robust optimization
(3)
model aggregation
(2)
gradient descent
(2)
randomized classifier
(2)
stochastic gradient descent
(2)
federated learning
(2)
adversarial attack
(2)
adversarial classification
(2)
distributed optimization
(1)
mean estimation
(1)
differential privacy
(1)
graph theory
(1)
convergence
(1)
game theory
(1)
multi-class classification
(1)
ensemble learning
(1)
Papers
On the Relevance of Byzantine Robust Optimization Against Data Poisoning
JMLR 2026
Unveiling the Role of Randomization in Multiclass Adversarial Classification: Insights from Graph Theory
AISTATS 2025
Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates
ICML 2024
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients
NeurIPS 2024
Revisiting Ensembling in One-Shot Federated Learning
NeurIPS 2024
Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity
AISTATS 2023
On the Privacy-Robustness-Utility Trilemma in Distributed Learning
ICML 2023
Robust Collaborative Learning with Linear Gradient Overhead
ICML 2023
Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity
NeurIPS 2023
Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums
ICML 2022
Towards Consistency in Adversarial Classification
NeurIPS 2022
Randomization matters How to defend against strong adversarial attacks
ICML 2020
Theoretical evidence for adversarial robustness through randomization
NeurIPS 2019