Definition
A technique used to stabilize the training of deep neural networks by scaling down the magnitude of the gradients when they exceed a predefined threshold, preventing "exploding gradients."
In short: A technique used to stabilize the training of deep neural networks by scaling down the magnitude of the gradients when they exceed a predefined threshold, preventing "exploding gradients.