11 citations · 27 across the 13 of their papers we have counts for
4 papers · 1 filter
To Ask or Not to Ask: Learning to Require Human Feedback
Andrea Pugnana, Giovanni De Toni, Cesare Barbera +3
Developing decision-support systems that complement human performance in classification tasks remains an open challenge. A popular approach, Learning to Defer (LtD), allows a Machi…
Multiclass Local Calibration with the Jensen-Shannon Distance
Cesare Barbera, Lorenzo Perini, Giovanni De Toni +2
Developing trustworthy Machine Learning (ML) models requires their predicted probabilities to be well-calibrated, meaning they should reflect true-class frequencies. Among calibrat…
Revisiting (Un)Fairness in Recourse by Minimizing Worst-Case Social Burden
Ainhize Barrainkua, Giovanni De Toni, Jose Antonio Lozano +1
Machine learning based predictions are increasingly used in sensitive decision-making applications that directly affect our lives. This has led to extensive research into ensuring…
You Don't Bring Me Flowers: Mitigating Unwanted Recommendations Through Conformal Risk Control
Giovanni De Toni, Erasmo Purificato, Emilia Gómez +3
Recommenders are significantly shaping online information consumption. While effective at personalizing content, these systems increasingly face criticism for propagating irrelevan…