2024
Gradient-Aware Logit Adjustment Loss for Long-Tailed Classifier
ICASSP 2024accepted
In the real-world setting, data often follows a long-tailed distribution, where head classes contain significantly more training samples than tail classes. Consequently, models trained on such data tend to be biased toward head classes. The medium of this bias is imbalanced gradients, which include…