Title :
A New Method for Large Scale Nonnegative Least Squares Problems
Author_Institution :
Dept. of Math., Shaanxi Univ. of Technol., Hanzhong, China
Abstract :
We present a new method for solving large scale nonnegative least squares problems. Firstly, nonnegative least squares problem was transformed into monotone linear complementarity problem. Then we apply potential-reduction interior point algorithm to monotone linear complementarity problem which is based on the Newton direction and centering direction. We show that this algorithm have the polynomial complexity. Numerical results are reported which demonstrate very good computational performance on nonnegative least squares problems.
Keywords :
Newton method; computational complexity; least squares approximations; polynomials; Newton direction; centering direction; computational performance; large scale nonnegative least squares problems; monotone linear complementarity problem; polynomial complexity; potential-reduction interior point algorithm; Convergence; Design optimization; Large-scale systems; Least squares methods; Mathematical programming; Mathematics; Polynomials; Quadratic programming; Vectors; large scale nonnegative least squares problem; monotone linear complementarity problem; polynomial complexity; potential-reduction interior point algorithm;
Conference_Titel :
Computer Technology and Development, 2009. ICCTD '09. International Conference on
Conference_Location :
Kota Kinabalu
Print_ISBN :
978-0-7695-3892-1
DOI :
10.1109/ICCTD.2009.88
