Machine Learning, Neural Networks, Statistics, Data Science, AI.
solutions, where more parameters will end up with a value of zero. Regularization, both with L¹ and L², also has a beautiful probabilistic interpretation: It is equivalent to adding a prior over the distribution of the weight matrix W; a Gaussian prior in the case of L², and a Laplacean prior in