报 告 人：周勇，华东师范大学教授

报告时间：2025.07.16  15:00-16:00

报告地点：苏州大学本部天元讲堂

报告摘要：In the context of the development of financial technology, we start with the complex characteristics of financial big data and elaborate on the importance of transfer learning of using multi-source data information to assist target tasks. We explain the significance of transfer learning technology in dealing with data heterogeneity from the perspective of multi-source data, and summarize the relevant concepts and methods of transfer learning technology, including data-driven and model-based transfer learning methods. In addition, this paper proposes the unified framework of transfer learning method in generalized moment estimation (GMM), gives the effective algorithm of transfer learning, and applies the proposed method to the application of transfer learning in risk value (VaR) and risk measure based on expected quantile (Expectile) under multi-source data. Then, we simulate two scenarios where samples are of insufficient or imbalanced sample sizes, respectively, in the application to personal bank credit evaluation, with tests of the prediction accuracy of three transfer learning methods, and analysis of the importance of filtering resource domain information. Finally, we described more application scenarios and development prospects of transfer learning in the financial field.

报告人简介：

   周勇教授，国家杰出青年基金获得者，教育部长江学者特聘教授，中国科学院百人计划入选者，国务院政府特殊津贴专家，“新世纪百千万人才工程”国家级人选，国际数理统计学会（IMS）会士。华东师范大学经管学部教授，统计学院院长，统计交叉科学研究院院长。曾任国务院学位委员会第七届统计学科评议组成员，教育部应用统计专业硕士教学指导委员会委员，中国优选法统筹法与经济数学研究会副理事长，现任中国管理科学学会常务理事、中国优选法统筹法与经济数学研究会常务理事。科技部重点研发计划项目首席科学家。

周勇教授主要从事大数据分析与建模、金融计量、风险管理、计量经济学、统计理论和方法等科学研究工作，取得许多有重要学术价值和影响的研究成果。先后承担并完成国家自然科学基金项目，国家杰出青年基金，自然科学基金委重点项目等科学项目10余项，科技部重点研发计划项目1项（首席科学家），曾获得省部级奖励二项。在包括国际顶级期刊《The Annals of Statistics》、《Journal of The American Statistical Association》，《Biometrika》，《JRSSB》及计量经济学顶刊《Journal of Econometrics》和《Journal of Business & Economic Statistics》及国内核心《管理科学学报》等学术杂志上发表学术论文近200余篇。