9月18日 张新雨教授学术报告(数学与统计学院)

文章作者:  发布时间: 2020-09-18  浏览次数: 10

报 告 人: 张新雨 教授

报告题目:Improve Machine Learning by Model Averaging

报告时间:2020年9月18日(周五)下午5:00 

报告地点:江苏师范大学数学与统计学院学术报告厅(静远楼1506室)

主办单位:数学与统计学院、科学技术研究院

报告人简介:

        张新雨,2010年在中科院系统所获博士学位,曾是TAMU博士后和PSU的Research Fellow,现为中科院数学与系统科学研究院研究员。担任期刊《Journal of Systems Science and Complexity》领域主编、期刊《Statistical Analysis and Data Mining》Associate Editor、期刊《系统科学与数学》和《应用概率统计》编委,是双法学会数据科学分会副理事长、国际统计学会当选会员和智源青年科学家。先后主持国家自然科学基金委优秀和杰出青年研究基金项目,曾获得中国管理学青年奖和中科院优秀博士学位论文等奖励。2020年8月,入选第十六届中国青年科技奖获奖人选名单。


报告摘要:

         This paper introduces novel methods to combine forecasts made by machine learning techniques. Machine learning methods have found many successful applications in predicting the response variable. However, they ignore model uncertainty when the relationship between the response variable and the predictors is nonlinear. To further improve the forecasting performance, we propose a general framework to combine multiple forecasts from machine learning techniques. Simulation studies show that the proposed machine-learning-based forecast combinations work well. In empirical applications to forecast key macroeconomic and financial variables, we find that the proposed methods can produce more accurate forecasts than individual machine learning techniques and the simple average method.