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← Authors

Rachid Guerraoui

29 papers · 2016–2025 · 6 conferences · across top CS/AI conferences

Achievements

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+13 more ↓ 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (10) 🌍 Conference Polyglot (6)
🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (9) 🌟 Keyword Trendsetter Combo (4) πŸ† Grand Slam πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion (4) 🀝 Dynamic Duo (12) ⚑ Prolific Year (7) πŸ—ƒοΈ Keyword Collector (104) πŸ’Ž Century Club (29) πŸ”₯ Unstoppable (6) πŸ“ˆ Trend Setter

Conferences

ICML (10) NIPS (7) AISTATS (4) OSDI (4) ICLR (3) AAAI (1)

Top co-authors

Youssef Allouah (12) Nirupam Gupta (9) Sadegh Farhadkhani (8) Rafael Pinot (8) John Stephan (6) LΓͺ-NguyΓͺn Hoang (4) El Mahdi El Mhamdi (4) SΓ©bastien Rouault (3) Geovani Rizk (3) El-Mahdi El-Mhamdi (3)

Research topics

Differential Privacy (2) Privacy (1)

Keywords

distributed learning (10) stochastic gradient descent (5) byzantine resilience (5) byzantine fault tolerance (4) decentralized learning (4) federated learning (4) differential privacy (3) adversarial robustness (3) model aggregation (3) data heterogeneity (3) gradient descent (3) consensus protocol (2) state machine replication (2) asynchronous algorithm (2) distributed machine learning (2) robust optimization (2) gradient aggregation (1) adversarial machine learning (1) ensemble learning (1) adversarial learning (1)

Papers

Adaptive Gradient Clipping for Robust Federated Learning ICLR 2025 Certified Unlearning for Neural Networks ICML 2025 Towards Trustworthy Federated Learning with Untrusted Participants ICML 2025 The Utility and Complexity of In- and Out-of-Distribution Machine Unlearning ICLR 2025 DSig: Breaking the Barrier of Signatures in Data Centers OSDI 2024 Revisiting Ensembling in One-Shot Federated Learning NIPS 2024 Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients NIPS 2024 Robust Sparse Voting AISTATS 2024 Byzantine-Robust Federated Learning: Impact of Client Subsampling and Local Updates ICML 2024 The Privacy Power of Correlated Noise in Decentralized Learning ICML 2024 Chop Chop: Byzantine Atomic Broadcast to the Network Limit OSDI 2024 On the Strategyproofness of the Geometric Median AISTATS 2023 Robust Distributed Learning: Tight Error Bounds and Breakdown Point under Data Heterogeneity NIPS 2023 Epidemic Learning: Boosting Decentralized Learning with Randomized Communication NIPS 2023 On the Privacy-Robustness-Utility Trilemma in Distributed Learning ICML 2023 Robust Collaborative Learning with Linear Gradient Overhead ICML 2023 Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity AISTATS 2023 Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums ICML 2022 An Equivalence Between Data Poisoning and Byzantine Gradient Attacks ICML 2022 Collaborative Learning in the Jungle (Decentralized, Byzantine, Heterogeneous, Asynchronous and Nonconvex Learning) NIPS 2021 Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent ICLR 2021 Differentially Private Stochastic Coordinate Descent AAAI 2021 Microsecond Consensus for Microsecond Applications OSDI 2020 The Hidden Vulnerability of Distributed Learning in Byzantium ICML 2018 Asynchronous Byzantine Machine Learning (the case of SGD) ICML 2018 Personalized and Private Peer-to-Peer Machine Learning AISTATS 2018 Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent NIPS 2017 Dynamic Safe Interruptibility for Decentralized Multi-Agent Reinforcement Learning NIPS 2017 Incremental Consistency Guarantees for Replicated Objects OSDI 2016