arXiv stat.ML
· Papers
Data Augmentation: A Fourier Analysis Perspective
arXiv:2606.24418v1 Announce Type: cross Abstract: Data augmentation is a simple and model-agnostic approach for exploiting known invariances in learning problems. Given a group acting on the input space, one augments the training set with transformed copies of each sample. Because it exploits symmetries without modifyi