4 citations · 7 across the 4 of their papers we have counts for
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cs.LG2024
Tackling Noisy Labels with Network Parameter Additive Decomposition
Jingyi Wang, Xiaobo Xia, Long Lan +5
Given data with noisy labels, over-parameterized deep networks suffer overfitting mislabeled data, resulting in poor generalization. The memorization effect of deep networks shows…
cs.LG2024★ 2 cited
Mitigating Label Noise on Graph via Topological Sample Selection
Yuhao Wu, Jiangchao Yao, Xiaobo Xia +4
Despite the success of the carefully-annotated benchmarks, the effectiveness of existing graph neural networks (GNNs) can be considerably impaired in practice when the real-world g…
cs.LG2023★ 4 cited
Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation
Jianing Zhu, Geng Yu, Jiangchao Yao +4
Out-of-distribution (OOD) detection is important for deploying reliable machine learning models on real-world applications. Recent advances in outlier exposure have shown promising…