Neyman-Pearson multiclass classification under label noise via empirical likelihood

Qiong Zhang, Qinglong Tian, Pengfei Li

In many classification problems, misclassification costs are highly asymmetric, while training labels are often corrupted due to measurement error, annotator variability, or advers…