Learning Optimal and Near-Optimal Lexicographic Preference Lists

19 Sep 2019Ahmed MoussaXudong Liu

We consider learning problems of an intuitive and concise preference model, called lexicographic preference lists (LP-lists). Given a set of examples that are pairwise ordinal preferences over a universe of objects built of attributes of discrete values, we want to learn (1) an optimal LP-list that decides the maximum number of these examples, or (2) a near-optimal LP-list that decides as many examples as it can... (read more)

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