Neural Collapse Inspired Attraction-Repulsion-Balanced Loss for Imbalanced Learning. (arXiv:2204.08735v1 [cs.LG])

Class imbalance distribution widely exists in real-world engineering.
However, the mainstream optimization algorithms that seek to minimize error
will trap the deep learning model in sub-optimums when facing extreme class
imbalance. It seriously harms the classification precision, especially on the
minor classes. The essential reason is that the gradients of the classifier
weights are imbalanced among the components from different classes. In this
paper, we propose Attraction-Repulsion-Balanced Loss (ARB-Loss) to balance the
different components of the gradients. We perform experiments …

arxiv learning loss neural collapse