Leveraging Label Proportion Prior for Class-Imbalanced Semi-Supervised Learning

Kohki Akiba, Shinnosuke Matsuo, Shota Harada +1

Semi-supervised learning (SSL) often suffers under class imbalance, where pseudo-labeling amplifies majority bias and suppresses minority performance. We address this issue with a…