SDLS is a Matlab freeware allowing to solve approximately
convex conic least-squares problems.
Geometrically, these problems amount to finding the projection
of a point onto the intersection of a symmetric convex cone
with an affine subspace.
SDLS solves the dual problem with a quasi-Newton
minimization algorithm, using an implementation
of the BFGS algorithm. The other key numerical
component is eigenvalue decomposition for
symmetric matrices, achieved by Matlab's built-in linear algebra
functions.
Note that SDLS may not be the most competitive implementation of
this algorithm. Our first goal
is to provide a **simple**, **user-friendly**
software for solving and experimenting with general conic
least-squares. Up to our knowledge, no
such freeware existed when releasing the first version
of SDLS.

Version history:

SDLS is developed for Matlab 7 and above, and distributed freely as a tar.gz archive, for research and academic purposes. Please contact the authors. The software is described in this documentation.

SDLS uses the BFGS algorithm of the HANSO package, which must be installed.

Last modified on 13 February 2009.