1.9k citations · 2.9k across the 29 of their papers we have counts for
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Diffusion-Driven High-Dimensional Variable Selection
Minjie Wang, Xiaotong Shen, Wei Pan
Variable selection for high-dimensional, highly correlated data has long been a challenging problem, often yielding unstable and unreliable models. We propose a resample-aggregate…
Causal Discovery with Generalized Linear Models through Peeling Algorithms
Minjie Wang, Xiaotong Shen, Wei Pan
This article presents a novel method for causal discovery with generalized structural equation models suited for analyzing diverse types of outcomes, including discrete, continuous…
Sparse Regression for Extreme Values
Andersen Chang, Minjie Wang, Genevera Allen
We study the problem of selecting features associated with extreme values in high dimensional linear regression. Normally, in linear modeling problems, the presence of abnormal ext…
Supervised Convex Clustering
Minjie Wang, Tianyi Yao, Genevera I. Allen
Clustering has long been a popular unsupervised learning approach to identify groups of similar objects and discover patterns from unlabeled data in many applications. Yet, coming…
Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data
Minjie Wang, Genevera I. Allen
In mixed multi-view data, multiple sets of diverse features are measured on the same set of samples. By integrating all available data sources, we seek to discover common group str…