Sparse Data Augmentation for Optimization with Provable Guarantees.

arXiv:2609.08133v2 Announce Type: replace-cross Abstract: In nonconvex optimization problems arising in geometric machine learning, data augmentation is commonly used to promote invariance by averaging empirical losses over transformations of the data. Computi