Academic Report of School of Mathematical Sciences [2026] No. 084

(Series Report for High-Level University Construction No. 1343)

Title：Homogeneity Pursuit in Ranking Inference Based on Pairwise Comparison

Speaker：Assistant Professor Tao Yuxin (Southern University of Science and Technology)

Time：16:30-17:30, Sept. 12, 2026

Location：Conference Room 305, Alumni Plaza

Abstract: The Bradley-Terry-Luce (BTL) model is one of the most celebrated models for ranking inference based on pairwise comparison data, ranking individuals by their latent preference scores. A critical question that arises is the uncertainty quantification for ranks. Intuitively, the relative ranks of two individuals become unreliable when their preference scores differ only subtly. In this paper, we explore the homogeneity of preference scores in the BTL model, which assumes that individuals cluster into groups with the same scores. We propose novel penalized maximum likelihood estimators (MLE) to simultaneously and rigorously perform estimation and clustering. We establish the statistical properties of the proposed methods and develop corresponding inference procedures. By leveraging this group structure, we achieve a faster convergence rate and sharper confidence intervals for the MLE of preference scores, providing new insight into the power of exploiting low-dimensional structures in high-dimensional settings. To address computational challenges, we further develop a majorized ADMM algorithm for efficient optimization with convergence guarantees. Extensive simulations and real data analyses, including NBA team rankings and statistical journal rankings, demonstrate the improved prediction performance and enhanced interpretability of our model.

Speaker Profile：Tao Yuxin is an assistant professor and Ph.D. advisor in the Department of Statistics and Data Science at Southern University of Science and Technology. He earned his Ph.D. from the Department of Statistics at Tsinghua University and was a visiting scholar at the Department of Statistics at Harvard University. His research focuses on financial econometrics, time series analysis, network data analysis, preference ranking, and the application of statistics in ecology and epidemiology. His work has been published in PNAS (Proceedings of the National Academy of Sciences), the Journal of Econometrics, Statistica Sinica, and other journals. She has led a National Natural Science Foundation of China (NSFC) Young Scientist Program (Category C) and a General Program grant from the Guangdong Provincial Natural Science Foundation. She has received the International Mathematical Statistics (IMS) New Researcher Travel Award, the IMS Hannan Graduate Student Travel Award, the Tsinghua University National Scholarship, and the Outstanding Paper Award at the Academic Symposium of the Beijing Society of Applied Statistics, among others.

Faculty and students are welcome to attend!

Invited by: Wang Jiangzhou

School of Mathematical Sciences

September 9, 2026