20 citations · 56 across the 24 of their papers we have counts for
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cs.LG2021★ 20 cited
Probabilistic Margins for Instance Reweighting in Adversarial Training
Qizhou Wang, Feng Liu, Bo Han +5
Reweighting adversarial data during training has been recently shown to improve adversarial robustness, where data closer to the current decision boundaries are regarded as more cr…
cs.LG2021
Learning with Group Noise
Qizhou Wang, Jiangchao Yao, Chen Gong +4
Machine learning in the context of noise is a challenging but practical setting to plenty of real-world applications. Most of the previous approaches in this area focus on the pair…
cs.LG2021★ 2 cited
Tackling Instance-Dependent Label Noise via a Universal Probabilistic Model
Qizhou Wang, Bo Han, Tongliang Liu +3
The drastic increase of data quantity often brings the severe decrease of data quality, such as incorrect label annotations, which poses a great challenge for robustly training Dee…