Corpus ID: 57373765

Convergence Rates of Gradient Descent and MM Algorithms for Generalized Bradley-Terry Models

@article{Vojnovic2019ConvergenceRO,
  title={Convergence Rates of Gradient Descent and MM Algorithms for Generalized Bradley-Terry Models},
  author={Milan Vojnovic and Seyoung Yun and Kaifang Zhou},
  journal={ArXiv},
  year={2019},
  volume={abs/1901.00150}
}
We show tight convergence rate bounds for gradient descent and MM algorithms for maximum likelihood estimation and maximum aposteriori probability estimation of a popular Bayesian inference method for generalized Bradley-Terry models. This class of models includes the Bradley-Terry model of paired comparisons, the Rao-Kupper model of paired comparisons with ties, the Luce choice model, and the Plackett-Luce ranking model. Our results show that MM algorithms have same convergence rates as… Expand

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