2021
On the Inherent Regularization Effects of Noise Injection During Training
ICML 2021spotlight
Randomly perturbing networks during the training process is a commonly used approach to improving generalization performance. In this paper, we present a theoretical study of one particular way of random perturbation, which corresponds to injecting artificial noise to the training data. We provide a…