3 papers
cs.LG2025
PASTA: A Unified Framework for Offline Assortment Learning
Juncheng Dong, Weibin Mo, Zhengling Qi +3
We study a broad class of assortment optimization problems in an offline and data-driven setting. In such problems, a firm lacks prior knowledge of the underlying choice model, and…
stat.ME2025
Minimax Regret Learning for Data with Heterogeneous Subgroups
Weibin Mo, Weijing Tang, Songkai Xue +2
Modern complex datasets often consist of various sub-populations with known group information. In the presence of sub-population heterogeneity, it is crucial to develop robust and…
stat.ME2025
Hub Detection in Gaussian Graphical Models
José Ã. Sánchez Gómez, Weibin Mo, Junlong Zhao +1
Graphical models are popular tools for exploring relationships among a set of variables. The Gaussian graphical model (GGM) is an important class of graphical models, where the con…