The geometry of invariant learning: an information-theoretic analysis of data augmentation and generalization

Abdelali Bouyahia, Frédéric LeBlanc, Mario Marchand

Data augmentation is one of the most widely used techniques to improve generalization in modern machine learning, often justified by its ability to promote invariance to label-irre…