Xun-Liang Cai

Stochastic Feature Averaging for Learning with Long-Tailed Noisy Labels

Deep neural networks have shown promising results on a wide variety of tasks using large-scale and well-annotated training datasets. However, data collected from real-world applications can suffer from two prevalent biases, i.e., long-tailed class distribution and label noise. Previous efforts on lo…