15 citations · 30 across the 16 of their papers we have counts for
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cs.LG2022★ 1 cited
Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning
Alex Tamkin, Margalit Glasgow, Xiluo He +1
What role do augmentations play in contrastive learning? Recent work suggests that good augmentations are label-preserving with respect to a specific downstream task. We complicate…
cs.LG2022
Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence
Margalit Glasgow, Colin Wei, Mary Wootters +1
A major challenge in modern machine learning is theoretically understanding the generalization properties of overparameterized models. Many existing tools rely on uniform convergen…