爱情岛论坛 学术报告[2026]066号

（高水平大学建设系列报告1325号）

报告题目：Orthogonalized Score Tests for Conditional Variable Significance in Deep Partial Linear Cox Models

报告人：郝美玲 教授  （对外经济贸易大学）

报告时间：2026年6月29日14:30—15:30

报告地点：爱情岛论坛 粤海校区汇星楼514会议室

报告摘要：Conditional statistical inference for high-dimensional survival data remains a fundamental yet challenging problem, particularly when the effects of nuisance variables are complex and difficult to specify parametrically. In this paper, we propose a Deep Partial Linear Cox model that leverages neural networks to flexibly capture nonlinear nuisance effects while preserving interpretability for variables of primary interest. To test the conditional significance of high-dimensional variable sets within this framework, we develop an orthogonalized score test that effectively removes the influence of estimated nuisance components, thereby achieving valid inference in the presence of complex data dependencies. Our method accommodates settings where the number of tested parameters exceeds the sample size, without imposing sparsity assumptions. We establish the limiting null distribution of the proposed test statistic. Extensive numerical studies and an application to the TCGA breast cancer dataset demonstrate the superior performance and practical utility of our approach.

报告人简介：郝美玲，对外经济贸易大学教授，香港理工大学博士，玛格丽特公主癌症研究中心博士后。主要研究领域：高维数据分析，生物统计，非参数统计，强化学习。主持国自然青年和面上基金项目，学术论文发表于Journal of the American Statistic Association, Journal of Machine Learning Research, Statistica Sinica, The Electronic Journal of Statistics, Computational Statistics & Data Analysis, Statistical Methods in Medical Research等期刊。

邀请人：胡宗良

爱情岛论坛

2026年6月24日