In this paper, we propose an iterative scheme for distributed Byzantineresilient estimation of a gradient associated with a black-box model. Our algorithm is based on simultaneous perturbation, secure state estimation and two-timescale stochastic approximations. We also show the performance of our algorithm through numerical experiments.

翻译：在本文中,我们提出一个迭代方案,用于对黑盒模型相关梯度进行分布式拜占庭静态估计。我们的算法基于同时的扰动、安全的状态估计和两次尺度的随机近似。我们还通过数字实验展示了我们的算法的性能。