This paper tackles the problem of model complexity in the context of additive models. Several methods have been proposed to estimate smoothing parameters, as well as to perform var...
Marta Avalos, Yves Grandvalet, Christophe Ambroise
A new method is proposed to estimate the nonlinear functions in an additive regression model. Usually, these functions are estimated by penalized least squares, penalizing the cur...
Abstract. We develop three new techniques to build on the recent advances in online learning with kernels. First, we show that an exponential speed-up in prediction time per trial ...
ORN Additive is a prototype tool that was developed to show how the gap between database modeling and implementation can be reduced—more specifically, to show how associations d...
Sparse additive models are families of d-variate functions with the additive decomposition f∗ = ∑j∈S f∗ j , where S is an unknown subset of cardinality s d. In this paper,...