(10 points) Consider the linear model yi = x, B + ; for i = 1, ..., n, where BE RP and ci ~N(0, 1). Suppose the prior distribution of the coefficients is i.i.d. Laplace distribution BK Laplace ( 0, NIH In class, we've seen that the MAP estimation of S is equivalent to Lasso regression with some parameter _ B = arg min n Find the value of 1. Remark: Recall that the pdf of X ~ Laplace(v, b) is ac - V fx (20) = 2b exp b