COMPUTE THE POSTERIOR OF w 1. Write the likelihood of w.
2. We define the same prior for all weights: N (0, a^(-1)), where a > 0. Write the Bayes formula that defines the posterior distribution of w.
3. Prove that computing the MAP estimate of w is equivalent to a regularized least square problem. Write the relation that relates a,σ^2 and λ that is the regularization parameter.