69 citations · 231 across the 22 of their papers we have counts for
7 papers · 1 filter
Rejoinder: Learning Optimal Distributionally Robust Individualized Treatment Rules
Weibin Mo, Zhengling Qi, Yufeng Liu
We thank the opportunity offered by editors for this discussion and the discussants for their insightful comments and thoughtful contributions. We also want to congratulate Kallus…
Learning Optimal Distributionally Robust Individualized Treatment Rules
Weibin Mo, Zhengling Qi, Yufeng Liu
Recent development in the data-driven decision science has seen great advances in individualized decision making. Given data with individual covariates, treatment assignments and o…
High dimensional precision medicine from patient-derived xenografts
Naim U. Rashid, Daniel J. Luckett, Jingxiang Chen +8
The complexity of human cancer often results in significant heterogeneity in response to treatment. Precision medicine offers potential to improve patient outcomes by leveraging th…
Stability Enhanced Large-Margin Classifier Selection
Will Wei Sun, Guang Cheng, Yufeng Liu
Stability is an important aspect of a classification procedure because unstable predictions can potentially reduce users' trust in a classification system and also harm the reprodu…
Simultaneous Clustering and Estimation of Heterogeneous Graphical Models
Botao Hao, Will Wei Sun, Yufeng Liu +1
We consider joint estimation of multiple graphical models arising from heterogeneous and high-dimensional observations. Unlike most previous approaches which assume that the cluste…
Joint Estimation of Multiple Dependent Gaussian Graphical Models with Applications to Mouse Genomics
Yuying Xie, Yufeng Liu, William Valdar
Gaussian graphical models are widely used to represent conditional dependence among random variables. In this paper, we propose a novel estimator for data arising from a group of G…
Large-Margin Classification with Multiple Decision Rules
Patrick K. Kimes, D. Neil Hayes, J. S. Marron +1
Binary classification is a common statistical learning problem in which a model is estimated on a set of covariates for some outcome indicating the membership of one of two classes…