3 papers
stat.ML2026
Single Index Bandits: Generalized Linear Contextual Bandits with Unknown Reward Functions
Yue Kang, Mingshuo Liu, Bongsoo Yi +4
Generalized linear bandits have been extensively studied due to their broad applicability in real-world online decision-making problems. However, these methods typically assume tha…
cs.LG2025
A Trainable Centrality Framework for Modern Data
Minh Duc Vu, Mingshuo Liu, Doudou Zhou
Measuring how central or typical a data point is underpins robust estimation, ranking, and outlier detection, but classical depth notions become expensive and unstable in high dime…
stat.ME2025
WISE: A Weighted Similarity Aggregation Test for Serial Independence
Qihua Zhu, Mingshuo Liu, Yuefeng Han +1
We propose a nonparametric test for serial independence that aggregates pairwise similarities of observations with lag-dependent weights. The resulting statistic is powerful to gen…