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主讲人 |
Xingdong Feng |
简介 |
<p><span style="font-size: small;"><span style="font-family: Arial;"><span lang="EN-US">Recently, large scale datasets appear frequently due to the development of techniques. Distributed computation has attracted attentions from statistician. Since quantile regression has been an effective alternative to the classic mean regression in many fields. However, computationally efficient quantile regression estimates for large scale datasets are less developed. In this paper, we consider an efficient ADMM estimate that could be implemented in a distributed manner, which can deal with large scale datasets. </span></span></span></p> |
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主讲人简介 |
<p class="MsoNormal"><span style="font-size: small;"><span style="font-family: Arial;"><span lang="EN-US">School of Statistics and Management, Shanghai University of Finance and Economics</span></span></span><span lang="EN-US" style="font-family:"Times New Roman","serif""><o:p></o:p></span></p>
<p><span style="font-size: small;"><span style="font-family: Arial;"><span lang="EN-US">Homepage</span>:<u><span style="color: blue;"> </span></u></span></span><u><span style="color:blue"><a href="http://ssm.shufe.edu.cn/Home/Index/teacher?id=68" target="_blank"><span style="font-size: small;"><span style="font-family: Arial;"><span style="color: blue;">http://ssm.shufe.edu.cn/Home/Index/teacher?id=68</span></span></span></a></span></u><o:p></o:p></p> |
期数 |
厦门大学高级计量经济学与统计学系列讲座2017春季学期第2讲（总第90讲） |
