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
— Forecasting the tide level in the Venezia lagoon is a very compelling task. In this work we propose a new approach to the learning of tide level time series based on the local ...
E. Canestrelli, P. Canestrelli, Marco Corazza, Mau...
This paper proposes an iterative methodology for real-time robust mosaic topology inference. It tackles the problem of optimal feature selection (optimal sampling) for global estim...
We consider the problem of selecting the best system using simulation-based ordinal optimization. This problem has been studied mostly in the context of light-tailed distributions...
Machine learning approaches offer some of the most cost-effective approaches to building predictive models (e.g., classifiers) in a broad range of applications in computational bio...