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[01-09] Graph Based Nonparametric Testing for High Dimensional Data

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  题目:Graph Based Nonparametric Testing for High Dimensional Data

  时间:2019年1月9日周三下午3:00

  地点:软件所5号楼708会议室

  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.

  报告人简介:

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