The Dying Relu Problem, Causes And Solutions

Rectified Linear Unit (ReLU) is a nonlinear activation function used in deep learning. It maps negative values to zero and returns positive values, making it faster than other activation functions. ReLU also solves the vanishing gradient problem because the derivative of the ReLU function is 0 or 1. However, ReLU may enter a dead state, where the outputs are 0, making it difficult to recover. In this case, the gradient fails to flow during backpropagation, which results in the weights not being updated.