Convergence Rates of Zeroth Order Gradient Descent for Łojasiewicz Functions
证明了零阶梯度下降算法在光滑和非光滑Łojasiewicz函数上的收敛速度，发现函数值收敛速度可快于梯度下降轨迹，对优化算法研究者有用。
We prove convergence rates of Zeroth-order Gradient Descent (ZGD) algorithms for Łojasiewicz functions. Our results show that for smooth Łojasiewicz functions with Łojasiewicz exponent larger than 0.5 and smaller than 1, the functions values can converge much faster than the (zeroth-order) gradient descent trajectory. Similar results hold for convex nonsmooth Łojasiewicz functions. History: Accepted by Antonio Frangioni, Area Editor for Design & Analysis of Algorithms–Continuous. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.0247 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2023.0247 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .