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Maximum Likelihood Estimation for Entity Ranking under Iterative Synthetic Data Augmentation
We study entity ranking and inference under the Bradley--Terry--Luce (BTL) model using pairwise comparisons collected over sparse comparison graphs. In practice, collecting high-quality human judgments can be expensive and time-consuming, motivating the use of synthetic data augmentation in model tr
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