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…
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Published5 h ago (Fri, 18 Sep 2026 04:00:00 GMT)
RetrievedFri, 18 Sep 2026 08:00:48 GMT via rss
ClassifiedFri, 18 Sep 2026 08:01:04 GMT by heuristic
AuthorBehrooz Tahmasebi, Melanie Weber