activity
20162023
most citedLearning Choice Functions with Gaussian Processes

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20232 cited

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…

cs.AI2022

Credal Valuation Networks for Machine Reasoning Under Uncertainty

Branko Ristic, Alessio Benavoli, Sanjeev Arulampalam

Contemporary undertakings provide limitless opportunities for widespread application of machine reasoning and artificial intelligence in situations characterised by uncertainty, ho…

stat.ML2021

Correlated Product of Experts for Sparse Gaussian Process Regression

Manuel Schürch, Dario Azzimonti, Alessio Benavoli +1

Gaussian processes (GPs) are an important tool in machine learning and statistics with applications ranging from social and natural science through engineering. They constitute a p…

quant-ph2016

Quantum rational preferences and desirability

Alessio Benavoli, Alessandro Facchini, Marco Zaffalon

We develop a theory of quantum rational decision making in the tradition of Anscombe and Aumann's axiomatisation of preferences on horse lotteries. It is essentially the Bayesian d…

cs.LG20161 cited

Statistical comparison of classifiers through Bayesian hierarchical modelling

Giorgio Corani, Alessio Benavoli, Janez Demšar +2

Usually one compares the accuracy of two competing classifiers via null hypothesis significance tests (nhst). Yet the nhst tests suffer from important shortcomings, which can be ov…