講座題目：Distributed Empirical Likelihood Inference with Massive Data
主 講 人：中國科學院數(shù)學與系統(tǒng)科學研究院 王啟華 教授
講座時間：2024年3月20日（周四）14：00
講座地點：6號學院樓402會議室
主辦單位：新葡萄8883官網(wǎng)AMG
摘 要：
Empirical likelihood is a very important nonparametric approach which is of wide application. However, it is hard and even infeasible to calculate the empirical log-likelihood ratio statistic with massive data. The main challenge is the calculation of the Lagrange multiplier. This motivates us to develop a distributed empirical likelihood method by calculating the Lagrange multiplier in a multi-round distributed manner. It is shown that the distributed empirical log-likelihood ratio statistic is asymptotically standard chi-squared under some mild conditions. The proposed algorithm is communication-efficient and achieves the desired accuracy in a few rounds. Further, the distributed empirical likelihood method is extended to the case of Byzantine failures. A machine selection algorithm is developed to identify the worker machines without Byzantine failures such that the distributed empirical likelihood method can be applied. The proposed methods are evaluated by numerical simulations and illustrated with an analysis of airline on-time performance study and a surface climate analysis of Yangtze River Economic Belt.
主講人簡介：
王啟華，中國科學院數(shù)學與系統(tǒng)科學研究院研究員，博士生導師，國家杰出青年基金獲得者，教育部“長江學者”獎勵計劃特聘教授，中科院“百人計劃”入選者。曾在北京大學與香港大學任教，先后訪問加拿大Carleton大學、美國California大學戴維斯分校、美國California大學洛杉磯分校、美國Yale大學、美國華盛頓大學、美國西北大學、德國Humboldt大學、澳大利亞國立大學及澳大利亞悉尼大學等十余所國際知名大學。主要從事缺失數(shù)據(jù)分析、高維數(shù)據(jù)統(tǒng)計分析及大規(guī)模數(shù)據(jù)統(tǒng)計分析等方面的研究。出版專著三部，在The Annals of Statistics, JASA及Biometrika等國際重要刊物發(fā)表論文140余篇，部分工作已產(chǎn)生持久的學術(shù)影響。曾主持國家杰出青年基金項目、重點項目及多項面上項目。是高維統(tǒng)計分會理事長，中國現(xiàn)場統(tǒng)計研究會與中國概率統(tǒng)計學會常務(wù)理事，先后是IMS-China和IBS-China委員會委員，是一些國際與國內(nèi)一些學術(shù)期刊編委及科學出版社出版的《現(xiàn)代數(shù)學基礎(chǔ)》與《統(tǒng)計與數(shù)據(jù)科學》叢書的編委。
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