|
主讲人 |
Weining Shen |
简介 |
<p class="MsoNormal"><span style="font-size: small;"><span style="font-family: Arial;"><span lang="EN-US" style="line-height: 107%;">Abstract: Modern applications have generated many data sets of complex nature, such as high dimensionality, heterogeneity and unknown structure of interest. In this talk, I will discuss a few recent projects on extending the idea behind traditional statistical methods such as the principal component analysis, expectation maximization, and mixture model, to accommodate challenges in those applications. Theoretical properties, numerical results, and applications in biomedical studies will be discussed. </span></span></span><span lang="EN-US" style="font-size:12.0pt;line-height:107%"><o:p></o:p></span></p> |
