A Ranking Model Motivated by Nonnegative Matrix Factorization with Applications to Tennis Tournaments

15 Mar 2019Rui XiaVincent Y. F. TanLouis FilstroffCédric Févotte

We propose a novel ranking model that combines the Bradley-Terry-Luce probability model with a nonnegative matrix factorization framework to model and uncover the presence of latent variables that influence the performance of top tennis players. We derive an efficient, provably convergent, and numerically stable majorization-minimization-based algorithm to maximize the likelihood of datasets under the proposed statistical model... (read more)

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