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cs.LG2022
Dynamic Loss For Robust Learning
Shenwang Jiang, Jianan Li, Jizhou Zhang +2
Label noise and class imbalance commonly coexist in real-world data. Previous works for robust learning, however, usually address either one type of the data biases and underperfor…
cs.LG2021
Delving into Sample Loss Curve to Embrace Noisy and Imbalanced Data
Shenwang Jiang, Jianan Li, Ying Wang +3
Corrupted labels and class imbalance are commonly encountered in practically collected training data, which easily leads to over-fitting of deep neural networks (DNNs). Existing ap…