报告人:李高荣 教授报告题目:High-dimensional Statistics and Large-Scale Inference with Graphical Nonlinear Knockoffs摘要:This talk first introduces some high-dimensional statistics, then introduces the recent work about graphical nonli...[详细]
报告(一)题目:Linear Inverse Problems with Positivity Restrictions (带正性约束之线性逆问题) 报告人:田国梁时间:2020年12月26日 14:00-15:00地点:腾讯会议 ID 111 232 663摘要:在统计教学与研究中, 逆向思维(Reverse Thinking)和发散思维(Diver...[详细]
题目:基于广义估计方程的复杂数据分析方法 报告人:秦国友时间:2020年12月11日 9:00-10:00地点:腾讯会议 ID 228 757 574主办单位:统计学院摘要:该报告基于广义估计方程,提出针对异常点、缺失值和测量误差的纵向数据的统计分析方法。讨论了相关估计的...[详细]
报告题目:Testing for conditional independence: a groupwise dimension reduction-based adaptive-to-model approach报告人:朱学虎 副教授报告摘要: In this paper, we propose an adaptive-to-model test for conditional independence through gro...[详细]
报告题目:Model averaging estimation for probability density functions报告人:邹国华 教授报告摘要: Extraction of information from data is critical in the age of data science. Theoretically probability density function provides comprehens...[详细]
报告题目:Deterministic Sampling of Expensive Posteriors Using Kullback-Leibler Divergence报告人:孙法省 教授报告摘要: This paper introduces a new way of discrete approximation a continuous probability distribution F into a set of repres...[详细]
报告题目:Large-Scale Datastreams Surveillance via Pattern-Oriented-Sampling报告人:邹长亮 教授报告摘要: Monitoring large-scale datastreams with limited resources has become increasingly important for real-time detection of abnormal acti...[详细]
报告题目:Wordlength enumerator for fractional factorial designs 报告人:唐煜 教授报告摘要:While the minimum aberration criterion is popular for selecting good designs with qualitative factors under an ANOVA model, the minimum β-abe...[详细]