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Diego Alovisetti

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#machine learning Preprint Oct 2026

Learning a Ranking from Human Feedback in Log-Concave Random Utility Models

We study the problem of recovering the ranking of a fixed set of items according to their unknown numerical utilities. At each interaction with the environment, a learner presents the item set to a human and receives comparative feedback of two types. Under full-ranking feedback, each interaction reveals a noisy rankin...

Diego Alovisetti, Marco Mussi, A. Metelli · 0 citations

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