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On Preference Learning Based on Sequential Bayesian Optimization with Pairwise Comparison. (arXiv:2103.13192v2 [cs.LG] UPDATED)
Jan. 17, 2022, 2:10 a.m. | Tanya Ignatenko, Kirill Kondrashov, Marco Cox, Bert de Vries
cs.LG updates on arXiv.org arxiv.org
User preference learning is generally a hard problem. Individual preferences
are typically unknown even to users themselves, while the space of choices is
infinite. Here we study user preference learning from information-theoretic
perspective. We model preference learning as a system with two interacting
sub-systems, one representing a user with his/her preferences and another one
representing an agent that has to learn these preferences. The user with
his/her behaviour is modeled by a parametric preference function. To
efficiently learn the preferences …
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