Rachid Guerraoui
30 papers · 2016–2026 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+12 more ↓ Show less ↑
🗺️ Taxonomy Completionist (42) 🌍 Conference Polyglot · Silver 🏃 Academic Marathon · Half 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
🔬
Deep Specialist
(12)
🏆
Grand Slam
🤝
Dynamic Duo
(12)
🌟
Keyword Trendsetter Combo
(4)
🏆
Keyword Champion
(4)
🧭
Keyword Pioneer
📈
Trend Setter
⚡
Prolific Year · Productive
🗃️
Keyword Collector
(134)
💎
Century Club · Bronze
🔥
Unstoppable · Bronze
🌈
Renaissance Researcher
(5)
Top co-authors
Research topics
Machine Learning
(25)
Optimization & Theory
(21)
Artificial Intelligence
(14)
Application Areas
(10)
Core AI
(9)
Learning Types
(7)
Computer Science
(6)
Learning Paradigms · Artificial Intelligence
(6)
Mathematics & Optimization
(5)
Learning Paradigms · Machine Learning
(5)
Applications
(4)
Optimization
(4)
Security & Privacy
(3)
Systems
(3)
Deep Learning
(2)
Keywords
distributed learning
(11)
stochastic gradient descent
(6)
byzantine resilience
(6)
federated learning
(6)
gradient descent
(5)
decentralized learning
(4)
differential privacy
(4)
adversarial robustness
(4)
byzantine fault tolerance
(4)
data heterogeneity
(3)
model aggregation
(3)
robust optimization
(3)
consensus protocol
(2)
asynchronous algorithm
(2)
data poisoning
(2)
convergence guarantee
(2)
fault tolerance
(2)
distributed machine learning
(2)
state machine replication
(2)
distributed momentum
(2)
Papers
On the Relevance of Byzantine Robust Optimization Against Data Poisoning
JMLR 2026
Adaptive Gradient Clipping for Robust Federated Learning
ICLR 2025
Certified Unlearning for Neural Networks
ICML 2025
The Utility and Complexity of In- and Out-of-Distribution Machine Unlearning
ICLR 2025
Towards Trustworthy Federated Learning with Untrusted Participants
ICML 2025
Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates
ICML 2024
Chop Chop: Byzantine Atomic Broadcast to the Network Limit
OSDI 2024
DSig: Breaking the Barrier of Signatures in Data Centers
OSDI 2024
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients
NeurIPS 2024
Revisiting Ensembling in One-Shot Federated Learning
NeurIPS 2024
Robust Sparse Voting
AISTATS 2024
The Privacy Power of Correlated Noise in Decentralized Learning
ICML 2024
Epidemic Learning: Boosting Decentralized Learning with Randomized Communication
NeurIPS 2023
Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity
AISTATS 2023
On the Privacy-Robustness-Utility Trilemma in Distributed Learning
ICML 2023
On the Strategyproofness of the Geometric Median
AISTATS 2023
Robust Collaborative Learning with Linear Gradient Overhead
ICML 2023
Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity
NeurIPS 2023
An Equivalence Between Data Poisoning and Byzantine Gradient Attacks
ICML 2022
Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums
ICML 2022
Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning)
NeurIPS 2021
Differentially Private Stochastic Coordinate Descent
AAAI 2021
Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent
ICLR 2021
Microsecond Consensus for Microsecond Applications
OSDI 2020
Asynchronous Byzantine Machine Learning (the case of SGD)
ICML 2018
Personalized and Private Peer-to-Peer Machine Learning
AISTATS 2018
The Hidden Vulnerability of Distributed Learning in Byzantium
ICML 2018
Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning
NeurIPS 2017
Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent
NeurIPS 2017
Incremental Consistency Guarantees for Replicated Objects
OSDI 2016