Linchao Pan

Learning with Open-world Noisy Data via Class-independent Margin in Dual Representation Space

Learning with Noisy Labels (LNL) aims to improve the model generalization when facing data with noisy labels, and existing methods generally assume that noisy labels come from known classes, called closed-set noise. However, in real-world scenarios, noisy labels from similar unknown classes, i.e., o…