Reduced rank approximation of matrices has hitherto been possible only by unweighted least squares. This paper presents iterative techniques for obtaining such approximations when weights are ...

Journal of Computational Mathematics, Vol. 33, No. 2 (March 2015), pp. 113-127 (15 pages) In this paper, a constrained distributed optimal control problem governed by a firstorder elliptic system is ...

Penalized least squares estimates provide a way to balance fitting the data closely and avoiding excessive roughness or rapid variation. A penalized least squares estimate is a surface that minimizes ...