Corpus ID: 219531847

Learning Mixtures of Plackett-Luce Models with Features from Top-$l$ Orders

@article{Zhao2020LearningMO,
  title={Learning Mixtures of Plackett-Luce Models with Features from Top-\$l\$ Orders},
  author={Zhi-Bing Zhao and L. Xia},
  journal={ArXiv},
  year={2020},
  volume={abs/2006.03869}
}
Plackett-Luce model (PL) is one of the most popular models for preference learning. In this paper, we consider PL with features and its mixture models, where each alternative has a vector of features, possibly different across agents. Such models significantly generalize the standard PL, but are not as well investigated in the literature. We extend mixtures of PLs with features to models that generate top-$l$ and characterize their identifiability. We further prove that when PL with features is… Expand
Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model

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