Semi-supervised Triply Robust Inductive Transfer Learning

IF 3 1区数学 Q1 STATISTICS & PROBABILITY

Journal of the American Statistical Association Pub Date : 2024-08-22 DOI:10.1080/01621459.2024.2393463

Tianxi Cai, Mengyan Li, Molei Liu

引用次数: 0

Abstract

In this work, we propose a Semi-supervised Triply Robust Inductive transFer LEarning (STRIFLE) approach, which integrates heterogeneous data from a label-rich source population and a label-scarce t...

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半监督三重稳健归纳迁移学习

在这项工作中，我们提出了一种半监督三重稳健归纳转发器学习（STRIFLE）方法，该方法整合了来自标签丰富的源群体和标签稀少的源群体的异构数据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of the American Statistical Association 数学-统计学与概率论

CiteScore

7.50

自引率

8.10%

发文量

168

审稿时长

12 months

期刊介绍： Established in 1888 and published quarterly in March, June, September, and December, the Journal of the American Statistical Association ( JASA ) has long been considered the premier journal of statistical science. Articles focus on statistical applications, theory, and methods in economic, social, physical, engineering, and health sciences. Important books contributing to statistical advancement are reviewed in JASA . JASA is indexed in Current Index to Statistics and MathSci Online and reviewed in Mathematical Reviews. JASA is abstracted by Access Company and is indexed and abstracted in the SRM Database of Social Research Methodology.