Question 1. (20 pts.) Given a training set with m examples, the standard form of the regularized loss function for linear regression is J()=2m1[i=1m(h(x(i))y(i))2+j=1nj2] Also, consider the following loss function which is in canonical form J()=(YX)T(YX)+T where features are represented as a matrix X (each row is an example and each column is an individual feature) and true target values are represented as a column vector Y. (a) Are the two functions J() and J() exactly equivalent? Explain briefly