We study robustness properties of some iterative gradient-based methods for strongly convex functions, as well as for the larger class of functions with sector-bounded gradients, under a relative error model. Proofs of the corresponding convergence rates are based on frequency-domain criteria for the stability of nonlinear systems. Applications are given to inexact versions of gradient descent and the Triple Momentum Method. To further emphasize the usefulness of frequency-domain methods, we derive improved analytic bounds for the convergence rate of Nesterov's accelerated method (in the exact setting) on strongly convex functions.
翻译:我们根据一个相对错误模型,研究一些以迭代梯度为基础的方法的稳健性特性,这些方法可用于很强的弯曲函数,以及具有部门梯度的较大型功能类别;相应的趋同率的证明依据的是非线性系统稳定性的频率域标准;对不确切的梯度下移和三动力法进行了应用;为了进一步强调频率-大陆法的有用性,我们为Nesterov加速法的加速法(精确设定)的趋同率(精确设定)在很强的螺旋函数上的趋同率获得了更好的分析界限。