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会议时间：2022年12月21日（周叁）19:00—21:00

会议地点：腾讯会议488-327-722

会议介绍：

报告1：微分方程中的KAM理论

报告人：邱汶华

报告时间：19:00-20:00

内容介绍：上世纪五、六十年代，由三位著名数学家 Kolmogorov，Arnold 和 Moser 建立起来的经典KAM理论是哈密顿系统理论发展的里程碑。在微分方程的摄动理论研究中，以 KAM 为工具来研究系统的可约化性是一个十分活跃的领域。约化问题是微分方程领域的一个重要组成部分，特别是对方程解的形式及结构的研究具有重要的意义。本次论坛将着重介绍拟周期领域和概周期领域的相关进展。

报告2：Conditional Characteristic Feature Screening for Massive Imbalanced Data

报告人：王平

报告时间：20:00-21:00

内容介绍：Using conditional characteristic function as a screening index, a new modelfree screening procedure is proposed to deal with variable screening problems in large-scale high-dimensional imbalanced data analysis. For binary response, our results show that the screening index under full data is proportional to the screening index under case-control sampling, an important sampling property for imbalanced data. This conclusion implies that we can apply this screening method to imbalanced data. Surely, the most appealing feature of the screening index is that it can be expressed as a simple linear combination of two first-order moments, so it is computationally simple. In addition, we successfully extend this method to multiple response. The theoretical properties are established under regularity conditions. To compare the performance of our method with its competitors,extensive simulations are conducted, which shows that the proposed procedure performs well in both the linear and nonlinear models. Finally, a real data analysis is investigated to further illustrate the effectiveness of the new method.

数学与统计学院

2022年12月19日