28 citations · 59 across the 13 of their papers we have counts for
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cs.LG2022★ 28 cited
Trustable Co-label Learning from Multiple Noisy Annotators
Shikun Li, Tongliang Liu, Jiyong Tan +2
Supervised deep learning depends on massive accurately annotated examples, which is usually impractical in many real-world scenarios. A typical alternative is learning from multipl…
cs.CV2022★ 23 cited
Selective-Supervised Contrastive Learning with Noisy Labels
Shikun Li, Xiaobo Xia, Shiming Ge +1
Deep networks have strong capacities of embedding data into latent representations and finishing following tasks. However, the capacities largely come from high-quality annotated l…