Krishi Chawda

Sleep-Like Replay Reduces Loss-Landscape Sharpness to Improve Generalization (Student Abstract)

One of the central challenges in deep learning is that models trained on new tasks often overfit and lose the ability to generalize. This issue arises because gradient descent often converges to solutions in regions of the loss landscape that are sharp near their minima. High sharpness leads to rapi