Two level minimization in multidimensional scaling

Multidimensional scaling is a technique for exploratory analysis of multidimensional data. The essential part of the technique is minimization of a multimodal function with unfavorable properties like invariants and non-differentiability. Recently a ...

We present a method which when applied to certain non-convex QP will locate the global minimum, all isolated local minima and some of the non-isolated local minima. The method proceeds by formulating a (multi) parametric convex QP in terms of the data of the ...

Compressed sensing using 1 minimization has been widely and successfully applied. To further enhance the sparsity, a non-convex and piecewise linear penalty is proposed. This penalty gives two different weights according to the order of the absolute ...