4 citations · 4 across the 3 of their papers we have counts for
4 papers
Dependable Exploitation of High-Dimensional Unlabeled Data in an Assumption-Lean Framework
Chao Ying, Siyi Deng, Yang Ning +2
Semi-supervised learning has attracted significant attention due to the proliferation of applications featuring limited labeled data but abundant unlabeled data. In this paper, we…
Test of Significance for High-dimensional Thresholds with Application to Individualized Minimal Clinically Important Difference
Huijie Feng, Jingyi Duan, Yang Ning +1
This work is motivated by learning the individualized minimal clinically important difference, a vital concept to assess clinical importance in various biomedical studies. We formu…
Optimal and Safe Estimation for High-Dimensional Semi-Supervised Learning
Siyi Deng, Yang Ning, Jiwei Zhao +1
We consider the estimation problem in high-dimensional semi-supervised learning. Our goal is to investigate when and how the unlabeled data can be exploited to improve the estimati…
Nonregular and Minimax Estimation of Individualized Thresholds in High Dimension with Binary Responses
Huijie Feng, Yang Ning, Jiwei Zhao
Given a large number of covariates , we consider the estimation of a high-dimensional parameter in an individualized linear threshold for a continuous variable ,…