• <u id="saeeq"><wbr id="saeeq"></wbr></u>
  • <s id="saeeq"><div id="saeeq"></div></s>
  • <u id="saeeq"></u>
  • <u id="saeeq"><noscript id="saeeq"></noscript></u>
  • <s id="saeeq"></s>
  • [01-09] Graph Based Nonparametric Testing for High Dimensional Data

    文章來源:  |  發布時間:2019-01-08  |  【打印】 【關閉

      

      題目:Graph Based Nonparametric Testing for High Dimensional Data

      時間:2019年1月9日周三下午3:00

      地點:軟件所5號樓708會議室

      摘要:

      This talk will focus on a common applied High-dimensional k-sample comparison problem. We constructed a class of easy-to-implement nonparametric distribution-free tests based on new statistical tools and unexplored connections with spectral graph theory. The test is shown to possess various desirable properties along with a characteristic exploratory flavor that has practical consequences. The numerical examples show that our method works surprisingly well under a broad range of situations.

      報告人簡介:

      Kaijun Wang is a PhD Candidate at the Department of Statistical Science, Temple University, working with Prof. Subhadeep Mukhopadyay.

  • <u id="saeeq"><wbr id="saeeq"></wbr></u>
  • <s id="saeeq"><div id="saeeq"></div></s>
  • <u id="saeeq"></u>
  • <u id="saeeq"><noscript id="saeeq"></noscript></u>
  • <s id="saeeq"></s>
  • 久久久综合香蕉尹人综合网