Simiao Zuo

ARCH: Efficient Adversarial Regularized Training with Caching

2021

Adversarial regularization can improve model generalization in many natural language processing tasks. However, conventional approaches are computationally expensive since they need to generate a perturbation for each sample in each epoch. We propose a new …