29 citations · 110 across the 21 of their papers we have counts for
5 papers · 1 filter
fable.intermittent: benchmarking probabilistic forecasting methods for intermittent time series
Stefano Damato, Lorenzo Zambon, Giorgio Corani +1
Intermittent time series are common in spare-parts demand and retail sales. Since the cost of forecast errors is typically asymmetric, decisions such as inventory control require t…
A tutorial on learning from preferences and choices with Gaussian Processes
Alessio Benavoli, Dario Azzimonti
Preference modelling lies at the intersection of economics, decision theory, machine learning and statistics. By understanding individuals' preferences and how they make choices, w…
Learning Choice Functions with Gaussian Processes
Alessio Benavoli, Dario Azzimonti, Dario Piga
In consumer theory, ranking available objects by means of preference relations yields the most common description of individual choices. However, preference-based models assume tha…
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…
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…