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学术报告:Completely positive tensor recovery with minimal nuclear value

报告嘉宾:周安娃   
报告时间:20181026日周五下午15:30

报告地点:西教五 416(理学院)

报告题目: Completely positive tensor recovery with minimal nuclear value

 

报告摘要: In this paper, we introduce the CP-nuclear value of a completely positive (CP) tensor and study its properties. A semidefinite relaxation algorithm is proposed for solving the minimal CP-nuclear-value tensor recovery. If a partial tensor is CP-recoverable, the algorithm can give a CP tensor recovery with the minimal CP-nuclear value, as well as a CP-nuclear decomposition of the recovered CP tensor. If it is not CP-recoverable, the algorithm can always give a certificate for that, when it is regular. Some numerical experiments are also presented.

 

报告人概况:周安娃,上海大学数学系师资博士后。20166月博士毕业于上海交通大学数学科学学院,主要研究方向为完全正规划、张量计算和多项式优化。在 Mathematical Programming SIAM Journal of Matrix Analysis and its ApplicationsMathematics of Operations Research等国际顶级学术期刊上发表SCI论文10余篇。荣获2016年度博士后创新人才支撑打算(当年全国数学学科仅7人获批),分别获2015年和2016年度上海市运筹学会优秀论文一等奖。主持中国博士后科学基金第60批面上资助一项,主持国家自然科学青年基金一项。

 

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