Re: Linear regression with constraint on the hypothesis set
Thank you, sir, I think I finally got it. So if I want to pin down a number of M weights, I just move the constant M terms to the y vector (subtracting from it), and I am left with a matrix X with d+1M columns (the column of ones may also be gone). The result will be a vector of d+1M weights.
