Self-discipline on multiple channels

1 code implementation • 27 Apr 2023 • Jiutian Zhao, Liang Luo, Hao Wang

Comparative experimental results on both datasets show that SMC-2 outperforms Label Smoothing Regularizaion and Self-distillation From The Last Mini-batch on all models, and outperforms the state-of-the-art Sharpness-Aware Minimization method on 83% of the models. Compatibility of SMC-2 and data augmentation experimental results show that using both SMC-2 and data augmentation improves the generalization ability of the model between 0. 28% and 1. 80% compared to using only data augmentation.

Data Augmentation