Publications associées à Empire byzantin

Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity

Rachid Guerraoui, Nirupam Gupta, John Stephan, Sadegh Farhadkhani, Youssef Allouah, Rafaël Benjamin Pinot

Byzantine machine learning (ML) aims to ensure the resilience of distributed learning algorithms to misbehaving (or Byzantine) machines. Although this problem received significant attention, prior works often assume the data held by the machines to be homo ...

PMLR2023

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search

Rachid Guerraoui, Andrei Kucharavy, Matteo Monti

Modern machine learning (ML) models are capable of impressive performances. However, their prowess is not due only to the improvements in their architecture and training algorithms but also to a drastic increase in computational power used to train them.|S ...

New York2023

Leaderless consensus

Rachid Guerraoui, Gauthier Jérôme Timothée Voron, Vincent Gramoli, Mihail Igor Zablotchi, Karolos Antoniadis, Antoine Philippe Matthieu Desjardins

Classic synchronous consensus algorithms are leaderless in that processes exchange proposals, choose the maximum value and decide when they see the same choice across a couple of rounds. Indulgent consensus algorithms are typically leader-based. Although t ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Byzantine consensus is Θ(n^2): the Dolev-Reischuk bound is tight even in partial synchrony!

Rachid Guerraoui, Jovan Komatovic, Pierre Philippe Civit, Manuel José Ribeiro Vidigueira, Vincent Gramoli, Seth Gilbert

The Dolev-Reischuk bound says that any deterministic Byzantine consensus protocol has (at least) quadratic (in the number of processes) communication complexity in the worst case: given a system with n processes and at most f < n/3 failures, any solution t ...

2023

On the Validity of Consensus

Rachid Guerraoui, Jovan Komatovic, Pierre Philippe Civit, Manuel José Ribeiro Vidigueira, Seth Gilbert

The Byzantine consensus problem involves.. processes, out of which t < n could be faulty and behave arbitrarily. Three properties characterize consensus: (1) termination, requiring correct (nonfaulty) processes to eventually reach a decision, (2) agreement ...

New York2023

Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums

Rachid Guerraoui, Nirupam Gupta, John Stephan, Sadegh Farhadkhani, Rafaël Benjamin Pinot

Byzantine resilience emerged as a prominent topic within the distributed machine learning community. Essentially, the goal is to enhance distributed optimization algorithms, such as distributed SGD, in a way that guarantees convergence despite the presence ...

PMLR2022

An Equivalence Between Data Poisoning and Byzantine Gradient Attacks

Rachid Guerraoui, Sadegh Farhadkhani, Oscar Jean Olivier Villemaud, Le Nguyen Hoang

To study the resilience of distributed learning, the “Byzantine" literature considers a strong threat model where workers can report arbitrary gradients to the parameter server. Whereas this model helped obtain several fundamental results, it has sometimes ...

PMLR2022

As easy as ABC: Optimal (A)ccountable (B)yzantine (C)onsensus is easy!

Rachid Guerraoui, Jovan Komatovic, Pierre Philippe Civit, Vincent Gramoli, Seth Gilbert

It is known that the agreement property of the Byzantine consensus problem among n processes can be violated in a non-synchronous system if the number of faulty processes exceeds t0 = ┌n/3┐ − 1 [10], [19]. In this paper, we investigate the accountable Byza ...

IEEE2022

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Empire byzantin

Planetary-Scale Byzantine Fault Tolerance

Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity

Cross-chain payment protocols with success guarantees

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search

Leaderless consensus

Byzantine consensus is Θ(n^2): the Dolev-Reischuk bound is tight even in partial synchrony!

On the Validity of Consensus

Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums

An Equivalence Between Data Poisoning and Byzantine Gradient Attacks

As easy as ABC: Optimal (A)ccountable (B)yzantine (C)onsensus is easy!

Graph Chatbot

Chattez avec Graph Search

Planetary-Scale Byzantine Fault Tolerance

Byzantine-Resilient Learning Beyond Gradients: Distributing Evolutionary Search

Leaderless consensus

As easy as ABC: Optimal (A)ccountable (B)yzantine (C)onsensus is easy!

Cross-chain payment protocols with success guarantees

Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums

An Equivalence Between Data Poisoning and Byzantine Gradient Attacks

On the Validity of Consensus

Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity

Byzantine consensus is Θ(n^2): the Dolev-Reischuk bound is tight even in partial synchrony!