Mallows ranking models: maximum likelihood estimate and regeneration
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Proceedings of the 36th International Conference on Machine Learning, PMLR 97:61256134, 2019.
Abstract
This paper is concerned with various Mallows ranking models. We study the statistical properties of the MLE of Mallows’ $\phi$ model. We also make connections of various Mallows ranking models, encompassing recent progress in mathematics. Motivated by the infinite top$t$ ranking model, we propose an algorithm to select the model size $t$ automatically. The key idea relies on the renewal property of such an infinite random permutation. Our algorithm shows good performance on several data sets.
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