Constrained least squares problems arise in many applications. Their memory and computation costs are expensive practice involving high-dimensional input data. We employ the so-called "sketching" strategy to project problem onto a space of much lower "sketching dimension" via random sketching matrix. The key idea is reduce dimension as possible while maintaining approximation accuracy. Tensor s...

given a set  of  points in the plane and a constant ,-center problem is to find two closed disks which each covers the whole , the diameter of the bigger one is minimized, and the distance of the two centers is at least . constrained -center problem is the -center problem in which the centers are forced to lie on a given line . in this paper, we first introduce -center problem and its constrain...

We presented the basic concepts for peakconstrained least-squares (PCLS) optimization in previous papers. We present advanced PCLS optimization concepts in this paper.