Hi,

I have a large-scale constrained(x >= 0) linear least square problem to solve. Since the scale is large, also the matrix A (as in Ax = b) is arranged in a very complicated way, instead of explicit input of A, I wish to provide a function that takes a vector X and returns A*X, which can save me a lot of memory and trouble for trying to fill in the huge matrix. I know this feature is available in LSMR, but they don’t offer constraints on X… Any suggestion what I should do? Thank you!