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cs.LG2022
Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise
Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman
Increasing the size of overparameterized neural networks has been a key in achieving state-of-the-art performance. This is captured by the double descent phenomenon, where the test…
cs.LG2022★ 10 cited
Investigating Why Contrastive Learning Benefits Robustness Against Label Noise
Yihao Xue, Kyle Whitecross, Baharan Mirzasoleiman
Self-supervised Contrastive Learning (CL) has been recently shown to be very effective in preventing deep networks from overfitting noisy labels. Despite its empirical success, the…