Lecture
This lecture delves into comparing L1 and L0 penalization in linear regression with orthogonal designs, emphasizing soft-thresholding vs hard-thresholding. It also explores greedy algorithms like Forward selection and Orthogonal Matching Pursuit, along with an empirical comparison of L0, L1, and L2 regularization methods.