We have seen many regularization term, here we revisit the ridge regularization: Ein(w)+CwTw, Ridge regularization, also known as L2 regularization, is a technique used in machine learning to prevent overfitting and improve the generalization of a model. A more general soft constraint is the Tikhonov regularization constraint wTTwC which can capture relationships among the wi (the matrix is the Tikhonov regularizer). - What should be to obtain the constraint q=0Qwq2C ? - What should be to obtain the constraint (q=0Qwq)2C ? In quiz-2, we try to solve the regularized least squares: Ein(w)=21n=1N{ynwTxn}2 - Please provide the regularized least squares in Tikhonov regularization constraint form. - Please provide the closed-form solution to the extension of the least-squares solution. Note that the detailed procedure is required or you will get ZERO points