Multiplying Block Matrices in Numpy
- by Ada Xu
Hi Everyone I am python newbie
I have to implement lasso L1 regression for a class assignment. This involves solving a quadratic equation involving block matrices.
minimize x^t * H * x + f^t * x
where x 0
Where H is a 2 X 2 block matrix with each element being a k dimensional matrix and x and f being a 2 X 1 vectors each element being a k dimension vector.
I was thinking of using nd arrays.
such that
np.shape(H) = (2, 2, k, k)
np.shape(x) = (2, k)
But I figured out that np.dot(X, H) doesn't work here.
Is there an easy way to solve this problem? Thanks in advance.
