12 citations · 22 across the 12 of their papers we have counts for
Showing 2021 · cs.LGShow all
2 papers · 2 filters
cs.LG2021
Learning with Noisy Labels via Sparse Regularization
Xiong Zhou, Xianming Liu, Chenyang Wang +3
Learning with noisy labels is an important and challenging task for training accurate deep neural networks. Some commonly-used loss functions, such as Cross Entropy (CE), suffer fr…
cs.LG2021★ 12 cited
Asymmetric Loss Functions for Learning with Noisy Labels
Xiong Zhou, Xianming Liu, Junjun Jiang +2
Robust loss functions are essential for training deep neural networks with better generalization power in the presence of noisy labels. Symmetric loss functions are confirmed to be…