In this paper we consider a regularization approach to variable selection when the regression function depends nonlinearly on a few input variables. The proposed method is based o...
Lorenzo Rosasco, Matteo Santoro, Sofia Mosci, Ales...
It is well-known that the applicability of Linear Discriminant Analysis (LDA) to high-dimensional pattern classification tasks such as face recognition (FR) often suffers from the...
Juwei Lu, Konstantinos N. Plataniotis, Anastasios ...
In this paper, we present a new method for texture classification which we call the regularized simultaneous autoregressive method (RSAR). The regularization technique is introduc...
A linear program has a unique least 2-norm solution provided that the linear program has a solution. To locate this solution, most of the existing methods were devised to solve cer...
A common problem in linear regression is that largely aberrant values can strongly influence the results. The least quartile difference (LQD) regression estimator is highly robus...
Thorsten Bernholt, Robin Nunkesser, Karen Schettli...