Mitigating the Impact of Labeling Errors on Training via Rockafellian Relaxation

Louis L. Chen, Bobbie Chern, Eric Eckstrand +2

Labeling errors in datasets are common, arising in a variety of contexts, such as human labeling, noisy labeling, and weak labeling (i.e., image classification). Although neural ne…