3 citations · 3 across the 6 of their papers we have counts for
6 papers
Bias-Aware External-Model-Assisted Inference in High-Dimensional Regression
Hongzhe Zhang, Hanxuan Ye, Hongzhe Li
In high-dimensional semi-supervised linear regression, prediction-powered inference (PPI) corrects an external predictor with a rectifier estimated from the labeled data. In a line…
Multicalibration Boosting: Theory, Convergence, and Transferability
Hanxuan Ye, Hongzhe Li
Multicalibration extends classical calibration by requiring predictions to be unbiased over a rich collection of functions, encompassing both prediction slices and subpopulations.…
Batch effect correction with sample remeasurement in highly confounded case-control studies
Hanxuan Ye, Xianyang Zhang, Chen Wang +2
Batch effects are pervasive in biomedical studies. One approach to address the batch effects is repeatedly measuring a subset of samples in each batch. These remeasured samples are…
Spline Estimation of Functional Principal Components via Manifold Conjugate Gradient Algorithm
Shiyuan He, Hanxuan Ye, Kejun He
Functional principal component analysis has become the most important dimension reduction technique in functional data analysis. Based on B-spline approximation, functional princip…
A Unified Analysis of Multi-task Functional Linear Regression Models with Manifold Constraint and Composite Quadratic Penalty
Shiyuan He, Hanxuan Ye, Kejun He
This work studies the multi-task functional linear regression models where both the covariates and the unknown regression coefficients (called slope functions) are curves. For slop…
A Modern Theory for High-dimensional Cox Regression Models
Hanxuan Ye, Xianyang Zhang, Huijuan Zhou
The proportional hazards model has been extensively used in many fields such as biomedicine to estimate and perform statistical significance testing on the effects of covariates in…