12 citations · 14 across the 10 of their papers we have counts for
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cs.LG2024★ 2 cited
Towards Macro-AUC oriented Imbalanced Multi-Label Continual Learning
Yan Zhang, Guoqiang Wu, Bingzheng Wang +3
In Continual Learning (CL), while existing work primarily focuses on the multi-class classification task, there has been limited research on Multi-Label Learning (MLL). In practice…
cs.CV2024
Diverse Teacher-Students for Deep Safe Semi-Supervised Learning under Class Mismatch
Qikai Wang, Rundong He, Yongshun Gong +4
Semi-supervised learning can significantly boost model performance by leveraging unlabeled data, particularly when labeled data is scarce. However, real-world unlabeled data often…
cs.CV2024
CLIP-driven Outliers Synthesis for few-shot OOD detection
Hao Sun, Rundong He, Zhongyi Han +3
Few-shot OOD detection focuses on recognizing out-of-distribution (OOD) images that belong to classes unseen during training, with the use of only a small number of labeled in-dist…