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stat.ML2026
Convergence analysis of a family of Zermelo-type iterations for the Bradley--Terry model
Ruijian Han, Ding Lu, Yiming Xu
Zermelo's algorithm is a classical method for computing the maximum likelihood estimator in the Bradley--Terry (BT) model, but its convergence can be slow in practice. To accelerat…
stat.ML2026
Variance-aware Reward Modeling with Anchor Guidance
Shuxing Fang, Ruijian Han, Liangyu Zhang +1
Standard Bradley--Terry (BT) reward models are limited when human preferences are pluralistic. Although soft preference labels preserve disagreement information, BT can only expres…
stat.ML2020
A General Pairwise Comparison Model for Extremely Sparse Networks
Ruijian Han, Yiming Xu, Kani Chen
Statistical inference using pairwise comparison data is an effective approach to analyzing large-scale sparse networks. In this paper, we propose a general framework to model the m…