Robust AUC Optimization under the Supervision of Clean Data. (arXiv:2211.11751v1 [cs.LG])

AUC (area under the ROC curve) optimization algorithms have drawn much
attention due to the incredible adaptability for seriously imbalanced data.
Real-world datasets usually contain extensive noisy samples that seriously
hinder the model performance, but a limited number of clean samples can be
obtained easily. Although some AUC optimization studies make an effort to
dispose of noisy samples, they do not utilize such clean samples well. In this
paper, we propose a robust AUC optimization algorithm (RAUCO) with good use …

arxiv auc clean data data optimization