Deep Learning, Regularisation, Optimization Algorithms, Deep Neural Networks, Gradient Descent.
does! If we set the regularization parameter (ƛ) to a large value, the decay in the weights during gradient descent update will be more. Hence, the weights of most of the hidden units will be close to zero. Since the weights are negligible, the model will not learn much from these units.This will