Reproduce “Bayesian Deck-of-cards-based Ordinal Regression with Sequential Preference Elicitation” on OpenResearch
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About this paper
Marco Grillo, Silvano Zappalà
The paper introduces B-DOR, which models a decision maker’s rankings and blank-card preference strengths as probabilistic evidence and updates recommendations across short sessions. Its BAYES-DOR and FTRL-DOR methods use preference direction and intensity, allowing later answers to revise estimates. In simulation, FTRL-DOR’s one-session ASR was 0.145 ± 0.004 versus 0.121 ± 0.004 for DOR; this evidence is synthetic, not human validation.
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