collaborators

6 papers

stat.ME2026

Multi-Source Prediction-Powered Inference

Wenhui Li, Fen Jiang, Xinyu Zhang

Prediction-powered inference integrates a small gold-standard dataset with large pseudo-labeled data, whose labels are generated by machine learning methods, to enhance statistical…

stat.ME2026

Identification and Inference for Structural Accelerated Failure Time Models via Instrument Interactions

Qiushi Bu, Wen Su, Xinyu Zhang +2

We study causal inference for time-to-event outcomes under right censoring in the presence of unmeasured confounding. Focusing on structural accelerated failure time models, we dev…

stat.ML2026

Constrained Bayesian Experimental Design via Online Planning

Yujia Guo, Daolang Huang, Xinyu Zhang +3

Bayesian experimental design (BED) is a principled framework for data-efficient design of sequential experiments. However, existing BED methods are unable to adapt to dynamic const…

stat.ME2026

Estimation of Directed Acyclic Graphs by Frequentist Model Averaging

Huihang Liu, Wenhui Li, Xinyu Zhang

Directed acyclic graphs provide a fundamental tool for representing directed dependence structures in multivariate network data, and are widely used to model financial and economic…

stat.ME2024

Semi-supervised learning using copula-based regression and model averaging

Ziwen Gao, Huihang Liu, Xinyu Zhang

The available data in semi-supervised learning usually consists of relatively small sized labeled data and much larger sized unlabeled data. How to effectively exploit unlabeled da…

stat.ME2024

Representation Transfer Learning for Semiparametric Regression

Baihua He, Huihang Liu, Xinyu Zhang +1

We propose a transfer learning method that utilizes data representations in a semiparametric regression model. Our aim is to perform statistical inference on the parameter of prima…