题    目：Online Estimation for Streaming Data: Methods, Theory, and Applications

主讲人：全明雪

单    位：中国人民大学

时    间：2025年9月26日 9:30

腾讯ID:  374-770-034

摘    要：Streaming data are continuously generated from diverse sources, characterized by an unknown total sample size, high velocity, sequential arrival, and typically the constraint of one-pass processing, which necessitate real-time analysis and rapid response. Classical statistical methods that require the entire dataset before modeling and analysis are difficult to handle such data. To address the challenges inherent in streaming data and further account for external resource constraints, we develop an efficient algorithm for online nonparametric estimation, systematically investigate its theoretical properties, and demonstrate its applicability using real data.

简    介：全明雪，2023年博士毕业于中国人民大学数学学院，现在中国人民大学应用数学研究中心从事博士后工作。研究方向为复杂结构数据分析以及非参数统计方法理论，目前的研究重点聚焦于流式数据的在线统计推断。部分研究成果发表在JASA，Communication in Statistics等期刊上，目前正在主持国家自然科学基金青年项目等共4项科研项目。