Multi resolution least squares SVM solver

Discusses the use of multi resolution analysis (MRA) for fast approximate solution of large linear sets of equations arising in least squares support vector machine (LS-SVM) problems. When LS-SVMs are used on a low dimensional input space, the matrix of the linear set exhibits a structure that leads to a sparse approximation in the wavelet domain. The amount of structure decreases with increasing dimensionality. We illustrate this principle by means of a small example.