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20152025
most citedShould we really use post-hoc tests based on mean-ranks?

155 citations · 170 across the 12 of their papers we have counts for

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cs.LG2025

The AI off-switch problem as a signalling game: bounded rationality and incomparability

Alessio Benavoli, Alessandro Facchini, Marco Zaffalon

The off-switch problem is a critical challenge in AI control: if an AI system resists being switched off, it poses a significant risk. In this paper, we model the off-switch proble…

cs.LG2024

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…

cs.LG2020

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…

cs.LG2020

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…

cs.LG2015155 cited

Should we really use post-hoc tests based on mean-ranks?

Alessio Benavoli, Giorgio Corani, Francesca Mangili

The statistical comparison of multiple algorithms over multiple data sets is fundamental in machine learning. This is typically carried out by the Friedman test. When the Friedman…