# A Nearly Instance Optimal Algorithm for Top-k Ranking under the Multinomial Logit Model

25 Jul 2017Xi ChenYuanzhi LiJieming Mao

We study the active learning problem of top-$k$ ranking from multi-wise comparisons under the popular multinomial logit model. Our goal is to identify the top-$k$ items with high probability by adaptively querying sets for comparisons and observing the noisy output of the most preferred item from each comparison... (read more)

PDF Abstract

No code implementations yet. Submit your code now