[08-26] Loyola University Maryland Jiyuan Tao教授学术报告

• 报告题目：On the independence of linear and quadratic forms in matrix Normal distribution and Wishart distribution

• 报告人：Jiyuan Tao教授，Loyola University Maryland

• 报告时间：8月26日上午9:00-10:00

• 报告地点：腾讯会议号：269-174-222

• 报告摘要：It is well-known that the Craig-Sakamoto theorem establishes the independence of two quadratic forms in Normal variates. Replacing the random Normal vectors by the random Normal matrices and Wishart variates, in this talk we present interconnections between the independence of linear forms, quadratic forms, trace forms in matrix Normal distribution and Wishart distribution. We show that the Craig-Sakamoto theorem still establishes the independence of two quadratic forms in matrix Normal distribution, but it does not establish the independence of two quadratic forms in Wishart variates.

报告人简介：Jiyuan Tao received his Ph.D. in Applied Mathematics, University of Maryland, Baltimore County, U.S.A. in 2004. He is a full professor in the Department of Mathematics and Statistics, Loyola University Maryland, U.S.A. He was also awarded “Distinguished Scholar of the Year, Loyola University Maryland (2018)”. Dr. Tao’s research field is in optimization, focusing on complementarity problems over symmetric cones and Euclidean Jordan algebras. He has been published in numerous prestigious peer-reviewed journals (e.g., Mathematical Programming, Mathematical Operations Research, Linear Algebra and its Applications, Linear and Multilinear Algebra). He provided invited talks in various international meetings. In addition, he has been a reviewer for several reputed journals such as Mathematical Programming, SIAM Optimization, Journal of Linear Algebra and its Applications, Journal of Optimization Theory and Applications.

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