Efficient Bilevel Optimization for Meta Label Correction in Noisy Label Learning

Training a deep neural network with noisy labels could reduce data annotation cost but may introduce noise into the learned model. In meta label correction approaches, an additional meta model besides the main model is trained with a small, clean dataset to correct the large, noisy dataset. To improve the training efficiency,