Random Smoothing Regularization in Kernel Gradient Descent Learning

no code implementations • 5 May 2023 • Liang Ding, Tianyang Hu, Jiahang Jiang, Donghao Li, Wenjia Wang, Yuan YAO

In this paper, we aim to bridge this gap by presenting a framework for random smoothing regularization that can adaptively and effectively learn a wide range of ground truth functions belonging to the classical Sobolev spaces.

Data Augmentation