Asynchronous Byzantine Machine Learning (the case of SGD)

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Planetary-Scale Byzantine Fault Tolerance

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The scale and pervasiveness of the Internet make it a pillar of planetary communication, industry and economy, as well as a fundamental medium for public discourse and democratic engagement. In stark contrast with the Internet's decentralized infrastructur ...

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Cross-chain payment protocols with success guarantees

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In this paper, we consider the problem of cross-chain payment whereby customers of different escrows-implemented by a bank or a blockchain smart contract-successfully transfer digital assets without trusting each other. Prior to this work, cross-chain paym ...

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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 ...

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Leaderless consensus

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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

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

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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 ...

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Rational Agreement in the Presence of Crash Faults

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Blockchain systems need to solve consensus despite the presence of rational users and failures. The notion of (k, t)-robustness is key to derive impossibility results with k rational players and t faulty players. However, these t faulty players are always ...

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Leaderless Consensus

Rachid Guerraoui, Vincent Gramoli, Mihail Igor Zablotchi, Karolos Antoniadis, Antoine Philippe Matthieu Desjardins

Classical synchronous consensus algorithms are leaderless: processes exchange their proposals, retain the maximum value and decide when they see the same choice across a couple of rounds. Indulgent consensus algorithms are more robust in that they only req ...

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Genuinely Distributed Byzantine Machine Learning

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Machine Learning (ML) solutions are nowadays distributed, according to the so-called server/worker architecture. One server holds the model parameters while several workers train the model. Clearly, such architecture is prone to various types of component ...

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Private and Secure Distributed Learning

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The ever-growing number of edge devices (e.g., smartphones) and the exploding volume of sensitive data they produce, call for distributed machine learning techniques that are privacy-preserving. Given the increasing computing capabilities of modern edge de ...

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The Performance of Byzantine Fault Tolerant Blockchains

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Blockchains have captured the attention of many, resulting in an abundance of new systems available for use. However, selecting an appropriate blockchain for an application is challenging due to the lack of comparative information discussing core metrics s ...

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