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arXiv · 2209.13095

Resilient Distributed Optimization

Jingxuan Zhu·Yixuan Lin·Alvaro Velasquez·Ji Liu
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Abstract

This paper considers a distributed optimization problem in the presence of Byzantine agents capable of introducing untrustworthy information into the communication network. A resilient distributed subgradient algorithm is proposed based on graph redundancy and objective redundancy. It is shown that the algorithm causes all non-Byzantine agents' states to asymptotically converge to the same optimal point under appropriate assumptions. A partial convergence rate result is also provided.

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Jingxuan Zhu, Yixuan Lin, Alvaro Velasquez, Ji Liu. 2022-09-27. Resilient Distributed Optimization. https://arxiv.org/abs/2209.13095

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