Yiling Xie

The Noise Premium in Adversarial Training for Kernel Regression

Noise premium makes the prediction error of adversarial training converge strictly more slowly than the nonparametric minimax benchmark even after balancing approximation and estimation errors, so the proposed noise-debiased adversarial training is proposed.