140 citations · 145 across the 9 of their papers we have counts for
7 papers · 1 filter
On the adaptation of recurrent neural networks for system identification
Marco Forgione, Aneri Muni, Dario Piga +1
This paper presents a transfer learning approach which enables fast and efficient adaptation of Recurrent Neural Network (RNN) models of dynamical systems. A nominal RNN model is f…
A Model-Agnostic Algorithm for Bayes Error Determination in Binary Classification
Umberto Michelucci, Michela Sperti, Dario Piga +2
This paper presents the intrinsic limit determination algorithm (ILD Algorithm), a novel technique to determine the best possible performance, measured in terms of the AUC (area un…
Deep learning with transfer functions: new applications in system identification
Dario Piga, Marco Forgione, Manas Mejari
This paper presents a linear dynamical operator described in terms of a rational transfer function, endowed with a well-defined and efficient back-propagation behavior for automati…
Preferential Bayesian optimisation with Skew Gaussian Processes
Alessio Benavoli, Dario Azzimonti, Dario Piga
Preferential Bayesian optimisation (PBO) deals with optimisation problems where the objective function can only be accessed via preference judgments, such as "this is better than t…
dynoNet: a neural network architecture for learning dynamical systems
Marco Forgione, Dario Piga
This paper introduces a network architecture, called dynoNet, utilizing linear dynamical operators as elementary building blocks. Owing to the dynamical nature of these blocks, dyn…
Skew Gaussian Processes for Classification
Alessio Benavoli, Dario Azzimonti, Dario Piga
Gaussian processes (GPs) are distributions over functions, which provide a Bayesian nonparametric approach to regression and classification. In spite of their success, GPs have lim…