min ||Ax-b||_2 with linear constraints

[ghost]

Hi All, I am wondering if spark-tfocs solves a linear regression problem with linear constraints. i.e.

min ||Ax-b||_2^2 s.t. Ux<=b where U is a matrix?

I know that it would solve without those constraints, but not sure if it handles the constraints.

[staple]

Hi mutmurat, unfortunately TFOCS for Spark does not support quadratic programming out of the box. However if your constraints happen to be very simple ranges you may be able to implement them using projection operators. (For example see the ProjBox operator.)

[ghost]

staple, thank you for the answer.

[akshaydse]

Hi can you please help me set up contraints lasso in py spark?