2 citations · 2 across the 3 of their papers we have counts for
3 papers
stat.ML2024
Beyond Unconstrained Features: Neural Collapse for Shallow Neural Networks with General Data
Wanli Hong, Shuyang Ling
Neural collapse (NC) is a phenomenon that emerges at the terminal phase of the training (TPT) of deep neural networks (DNNs). The features of the data in the same class collapse to…
cs.LG2024★ 2 cited
Cross Entropy versus Label Smoothing: A Neural Collapse Perspective
Li Guo, George Andriopoulos, Zifan Zhao +3
Label smoothing loss is a widely adopted technique to mitigate overfitting in deep neural networks. This paper studies label smoothing from the perspective of Neural Collapse (NC),…
stat.ML2023
Neural Collapse for Unconstrained Feature Model under Cross-entropy Loss with Imbalanced Data
Wanli Hong, Shuyang Ling
Recent years have witnessed the huge success of deep neural networks (DNNs) in various tasks of computer vision and text processing. Interestingly, these DNNs with massive number o…