Title: An analysis of the SPARSEVA estimate for the finite sample data case,
Abstract: In this paper, we develop an upper bound for the SPARSEVA (SPARSe Estimation
based on a VAlidation criterion) estimation error in a general scheme, i.e.,
when the cost function is strongly convex and the regularized norm is
decomposable for a pair of subspaces. We show how this general bound can be
applied to a sparse regression problem to obtain an upper bound for the
traditional SPARSEVA problem. Numerical results are used to illustrate the
effectiveness of the suggested bound.