Loss Functions for Linear Regression $(6$ points$)$: Assume that the hypothesis function is f$($w$,$ b$,$ x$)=$ wT x $+$ b$.$ In the standard linear regression case, given an instance xi$,$ yi on the training set, the loss function is defined as Li$($w$,$ b$)=[$f$($w$,$ b$,$ xi$)$ yi$]2.$ Imagine that we are still interested in posing the optimization problem $($over the dataset$)$ as: