Loss Functions and Prior Distributions

Andrew Gelman has an article that explains the relationship between loss functions and prior distributions. In a word, using L2 or L1 norm as regularisers for regresion is essentially equivalent to choosing Gaussian or Laplace priors for the parameters, i.e., L2 or L1 corresponds to the MAP of Gaussian or Laplace.