Data in the real-world classification problems are always imbalanced or
long-tailed, wherein the majority classes have the most of the samples that
dominate the model training. In such setting, the naive model tends to have
poor performance on the minority classes. Previously, a variety of loss
modifications have been proposed to address the long-tailed lean