Stretching the Effectiveness of MLE from Accuracy to Bias for Pairwise Comparisons

10 Jun 2019Jingyan WangNihar B. ShahR. Ravi

A number of applications (e.g., AI bot tournaments, sports, peer grading, crowdsourcing) use pairwise comparison data and the Bradley-Terry-Luce (BTL) model to evaluate a given collection of items (e.g., bots, teams, students, search results). Past work has shown that under the BTL model, the widely-used maximum-likelihood estimator (MLE) is minimax-optimal in estimating the item parameters, in terms of the mean squared error... (read more)

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