3 citations · 5 across the 9 of their papers we have counts for
9 papers
Trustworthy AI/ML Regression and Unbiased Causal Inference for Real-World Data
Yifei Xu, Hwiyoung Lee, Zhenyao Ye +5
Real-World Data (RWD), with its large sample sizes and rich clinical detail, offers a compelling alternative to randomized controlled trials (RCTs) for studying treatment effects i…
Outcome-Calibrated Regression and Predicted Outcome-Based Inference
Hwiyoung Lee, Shuo Chen
Regression is a fundamental tool in scientific research. Ordinary least squares (OLS), one of the most widely used regression methods, enjoys several desirable properties, includin…
Modeling Dependence in Omics Association Analysis via Structured Co-Expression Networks to Improve Power and Replicability
Hwiyoung Lee, Yezhi Pan, Shuo Chen
Accounting for dependence among high-dimensional variables in omics data analysis is critical to obtain accurate and reliable statistical inference. Although latent, omics variable…
Graph Canonical Correlation Analysis
Hongju Park, Shuyang Bai, Zhenyao Ye +3
Canonical correlation analysis (CCA) is a widely used technique for estimating associations between two sets of multi-dimensional variables. Recent advancements in CCA methods have…
A Systematic Bias of Machine Learning Regression Models and Its Correction: an Application to Imaging-based Brain Age Prediction
Hwiyoung Lee, Shuo Chen
Machine learning models for continuous outcomes often yield systematically biased predictions, particularly for values that largely deviate from the mean. Specifically, predictions…
Modeling Interconnected Modules in Multivariate Outcomes: Evaluating the Impact of Alcohol Intake on Plasma Metabolomics
Yifan Yang, Chixiang Chen, Hwiyoung Lee +2
Alcohol consumption has been shown to influence cardiovascular mechanisms in humans, leading to observable alterations in the plasma metabolomic profile. Regression models are comm…
Robust Extrinsic Regression Analysis for Manifold Valued Data
Hwiyoung Lee
Recently, there has been a growing need in analyzing data on manifolds owing to their important role in diverse fields of science and engineering. In the literature of manifold-val…
Extrinsic Kernel Ridge Regression Classifier for Planar Kendall Shape Space
Hwiyoung Lee, Vic Patrangenaru
Kernel methods have had great success in Statistics and Machine Learning. Despite their growing popularity, however, less effort has been drawn towards developing kernel based clas…
Anti-MANOVA on Compact Manifolds with Applications to 3D Projective Shape Analysis
Hwiyoung Lee, Vic Patrangenaru
Methods of hypotheses testing for equality of extrinsic antimeans on compact manifolds are unveiled in this paper. The two and multiple sample problem for antimeans on compact mani…