Results 1 
3 of
3
SOLVING A SEQUENCE OF SPARSE LEAST SQUARES PROBLEMS
"... We describe how to maintain an explicit sparse orthogonal factorization in order to solve the sequence of sparse least squares subproblems needed to implement an activeset method to solve the nonnegative least squares problem for a matrix with more columns than rows. In order to do that, we have ad ..."
Abstract

Cited by 6 (1 self)
 Add to MetaCart
We describe how to maintain an explicit sparse orthogonal factorization in order to solve the sequence of sparse least squares subproblems needed to implement an activeset method to solve the nonnegative least squares problem for a matrix with more columns than rows. In order to do that, we have adapted the sparse direct methodology of Björck and Oreborn of late 80s in a similar way to Coleman and Hulbert, but without forming the hessian matrix that is only positive semidefinite in this case. We comment on our implementation on top of the sparse toolbox of Matlab 5, and we emphasize the importance of Lawson and Hanson’s NNLS activeset method as an alternative to Dax’s constructive proof of Farkas ’ lemma; these methods can be used as Phase I for a nonsimplex activeset linear programming method.