zeronorm
zeronorm is a term that can refer to several concepts, often related to data normalization or initialization in different fields. In the context of machine learning, especially deep learning, zeronorm typically refers to a specific initialization technique for the weights of a neural network. This method aims to set the initial weights of a layer such that the variance of the activations is preserved across layers. Without proper initialization, gradients can either explode or vanish during training, hindering the learning process.
The zeronorm initialization strategy is designed to mitigate these issues. It often involves setting weights to
Beyond neural network initialization, the term zeronorm might be used in other contexts where the goal is