Byzantine-Robust Gossip: Insights from a Dual Approach

Renaud Gaucher; Aymeric Dieuleveut; Hadrien Hendrikx

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arXiv · 2405.03449

Byzantine-Robust Gossip: Insights from a Dual Approach

Renaud Gaucher·Aymeric Dieuleveut·Hadrien Hendrikx

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Abstract

Distributed learning has many computational benefits but is vulnerable to attacks from a subset of devices transmitting incorrect information. This paper investigates Byzantine-resilient algorithms in a decentralized setting, where devices communicate directly in a peer-to-peer manner within a communication network. We leverage the so-called dual approach for decentralized optimization and propose a Byzantine-robust algorithm. We provide convergence guarantees in the average consensus subcase, discuss the potential of the dual approach beyond this subcase, and re-interpret existing algorithms using the dual framework. Lastly, we experimentally show the soundness of our method.

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BibTeX RIS

Renaud Gaucher, Aymeric Dieuleveut, Hadrien Hendrikx. 2024-05-06. Byzantine-Robust Gossip: Insights from a Dual Approach. https://arxiv.org/abs/2405.03449

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