1 code implementation • 17 Oct 2023 • Uri Stern, Daniel Shwartz, Daphna Weinshall
Our method allows for the incorporation of useful knowledge obtained by the models during the overfitting phase without deterioration of the general performance, which is usually missed when early stopping is used.
no code implementations • 17 Oct 2023 • Uri Stern, Daphna Weinshall
An extensive empirical evaluation with modern deep models shows our method's utility on multiple datasets, neural networks architectures and training schemes, both when training from scratch and when using pre-trained networks in transfer learning.
no code implementations • 2 Oct 2022 • Daniel Shwartz, Uri Stern, Daphna Weinshall
This introduces a problem when training in the presence of noisy labels, as the noisy examples cannot be distinguished from clean examples by the end of training.