E C E 532

CS/ECE/ME 532 Homework 6: Iterative Algorithms for Regularized LS 1. Gradient Descent Convergence. Consider the Gradient Descent iteration for solving a standard least-squares problem with A ∈ R m×n , b ∈ R m, and A has full column rank. Recall that this iteration begins with some initial x0 and then: xk+1 = xk − µAT (Axk − b) for k = 0, 1, . . . (1) a) We expect the algorithm to converge to x? = (ATA) −1ATb. Define the error as ek := xk − x?. Show how to rewrite (1) in...