Ranking items based on pairwise comparisons, such as using match outcomes to rank sports teams, is a common task that becomes challenging when data is limited or noisy. Here, the authors introduce an efficient nonparametric Bayesian method for learning partial rankings that breaks ties among item ranks only when supported by sufficient statistical evidence in the data.
- Sebastian Morel-Balbi
- Alec Kirkley