In real-world applications, perfect labels are rarely available, making ...
Immune repertoire classification, a typical multiple instance learning (...
Modern neural networks are known to give overconfident prediction for
ou...
Learning with Noisy Labels (LNL) has attracted significant attention fro...
As an important part of intelligent transportation systems, traffic
fore...
Detecting out-of-distribution (OOD) samples is crucial to the safe deplo...
Noisy labels damage the performance of deep networks. For robust learnin...
Conventional unsupervised domain adaptation (UDA) methods need to access...
Co-training, extended from self-training, is one of the frameworks for
s...