应兰州大学数学与统计学院邀请，中国科学技术大学管理学院徐福芝博士将于2026年4月24日上午举行线上学术报告。

报告题目:Prediction-Powered Linear Regression: A Balance Between Interpretation and Prediction

时 间：2026年4月24日（星期五）10：00

腾讯会议ID：850 101 543

报告摘要：Unlabeled data are increasingly prevalent in contemporary economic studies, yet their effective use for improving prediction remains challenging because the outcomes are often costly or even infeasible to observe. Machine learning methods can help label these data and achieve high predictive accuracy, but they often lack interpretability. In this paper, we propose a Prediction-powered Unified Model Averaging (PUMA) framework to combine linear regression and machine learning methods, achieving a balance between interpretation and prediction. Unlike existing works on prediction-powered inference, our approach is the first to jointly address uncertainty arising from model misspecification, power-tuning selection, and the choice of machine learning algorithms by using model averaging. Theoretically, we establish the asymptotic prediction optimality of the proposed method both in-sample and out-of-sample under mild conditions, along with estimation consistency. Extensive simulations and a real-world application further demonstrate the empirical advantages of the proposed method.

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报告人简介

徐福芝博士，博士毕业于厦门大学王亚南经济研究院统计学专业，现于中国科学技术大学管理学院从事博士后研究，主要研究方向为模型平均、多源数据整合分析、迁移学习等。近年来主持博士后面上基金一项，参与国家自然科学基金重大项目及面上项目多项，共发表论文5篇（SCI 3篇，CSSCI 2篇）。

数学与统计学院

甘肃应用数学中心

甘肃省高校应用数学与复杂系统省级重点实验室 萃英学院

2026年4月20日