2 papers
cs.LG2023
Partial-Label Regression
Xin Cheng, Deng-Bao Wang, Lei Feng +2
Partial-label learning is a popular weakly supervised learning setting that allows each training example to be annotated with a set of candidate labels. Previous studies on partial…
cs.LG2021
Learning from Noisy Labels via Dynamic Loss Thresholding
Hao Yang, Youzhi Jin, Ziyin Li +4
Numerous researches have proved that deep neural networks (DNNs) can fit everything in the end even given data with noisy labels, and result in poor generalization performance. How…