activity
20182022
most citedSparse Laplacian Shrinkage with the Graphical Lasso Estimator for Regression Problems

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

stat.ME2022

Dimension reduction of high-dimension categorical data with two or multiple responses considering interactions between responses

Yuehan Yang

This paper models categorical data with two or multiple responses, focusing on the interactions between responses. We propose an efficient iterative procedure based on sufficient d…

stat.ME2020

Interaction Pursuit Biconvex Optimization

Yuehan Yang, Siwei Xia, Hu Yang

Multivariate regression models are widely used in various fields such as biology and finance. In this paper, we focus on two key challenges: (a) When should we favor a multivariate…

stat.ME20191 cited

Sparse Laplacian Shrinkage with the Graphical Lasso Estimator for Regression Problems

Yuehan Yang, Siwei Xia, Hu Yang

This paper considers a high-dimensional linear regression problem where there are complex correlation structures among predictors. We propose a graph-constrained regularization pro…

stat.ME2019

Smooth Adjustment for Correlated Effects

Yuehan Yang, Hu Yang

This paper considers a high dimensional linear regression model with corrected variables. A variety of methods have been developed in recent years, yet it is still challenging to k…

stat.ME2018

MSP: A Multi-step Screening Procedure for Sparse Recovery

Yuehan Yang, Ji Zhu, Edward I. George

We propose a Multi-step Screening Procedure (MSP) for the recovery of sparse linear models in high-dimensional data. This method is based on a repeated small penalty strategy that…

math.ST2018

Penalized regression adjusted causal effect estimates in high dimensional randomized experiments

Hanzhong Liu, Yuehan Yang

Regression adjustments are often considered by investigators to improve the estimation efficiency of causal effect in randomized experiments when there exists many pre-experiment c…