题目:EXPECTED L_2-DISCREPANCY FOR A CLASS OF NEW STRATIFIED SAMPLING MODELS
报告人:冼军
讲座时间:2022年11月9日(周三)15:00-16:00
地点:线上腾讯会议:730-558-675 ,线下会议:综合楼644
摘要:We introduce a class of convex equivolume partitions, among this class, there exists an optimal partition manner. Expected L_2-discrepancy are discussed under these partitions. There are two main results. First, under this kind of partitions, we generate random point sets with smaller expected L_2-discrepancy than classical jittered sampling for the same sampling number. Further, among these new partitions, there is the optimal partition for the expected L_2-discrepancy. Second, an explicit expected L_2-discrepancy upper bound under this kind of partitions is also given.
报告人简介:冼军,男,博士,博士生导师,国家级高层次青年人才称号获得者(2014年),2004年于中山大学获理学博士学位,2006年于浙江大学数学博士后流动站出站,入职中山大学数学学院,任副教授,2015年于中山大学晋升为教授。目前兼任中国数学会理事,广东省数学会理事,广东省工业与应用数学会副理事长。主持多项国家级和省部级基金项目,曾在本领域主流期刊发表多篇学术论文,如ACHA,IP,PAMS,JFAA,JAT,SP等,研究兴趣为随机样本的采样与函数重构、图采样与重构及其应用、学习理论及其应用等。
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