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'Smart_aug' objective is to make data augmentation differentiable, thus allowing to learn its parameters, with 'Higher' objects, such as 'Data_aug' classes. The meta-learning of the data augmentation parameter is performed jointly with the training of the model. Thus it minimize the overhead compared to other data augmentation learning techniques.
| FAR-HO | ||
| Gradient-Descent-The-Ultimate-Optimizer | ||
| higher | ||
| PBA | ||
| UDA | ||
| .gitignore | ||
