A class of preconditioners for weighted least squares problems
Reports in Informatics No. 170, May 1999, Department of
Informatics, University of Bergen, Norway.
We consider solving a sequence of weighted linear least squares
problems where the changes from one problem to the next are the
weights and the right hand side (or data). This is the case for
primal-dual interior-point methods. We derive a class of
preconditioners based on a low rank correction to a Cholesky
factorization of a weighted normal equation coefficient matrix with
the previous weight.