Resilient Distributed Optimization
Optimization and Control
2023-03-22 v2 Systems and Control
Systems and Control
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.
Cite
@article{arxiv.2209.13095,
title = {Resilient Distributed Optimization},
author = {Jingxuan Zhu and Yixuan Lin and Alvaro Velasquez and Ji Liu},
journal= {arXiv preprint arXiv:2209.13095},
year = {2023}
}
Comments
This version fixes the incorrect statements of Proposition 3 and Theorem 2 in the last version