We discuss the problem of overfitting of probabilistic neural networks in the framework of statistical pattern recognition. The probabilistic approach to neural networks provides a...
Increasing applications are demanding effective and efficient support to perform retrieval in large collections of digital images. The work presented here is an early stage resear...
Giovanna Castellano, Gianluca Sforza, Maria Alessa...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
The criterion of total weighted completion time occurs as a sub-problem of combinatorial optimization problems in such diverse areas as scheduling, container loading and storage a...
Recent results have suggested that online Model Predictive Control (MPC) can be computed quickly enough to control fast sampled systems. High-speed applications impose a hard real-...
Melanie Nicole Zeilinger, Colin Neil Jones, Davide...