学术报告
报告题目：On Two Matrix Optimization Problems: Correlation vs Euclidean
Distance
报告人: Houduo Qi
( School of Mathematical Sciences, University of Southampton, UK)
报告时间: 2016年7月29日上午9:00-10:00
报告地点: 创新园大厦A1101
报告校内联系人：张立卫教授 (联系电话：84708351-8118)
报告摘要: Matrix optimization has recently taken a new shape from a numerical perspective, where Semismooth
Newton-CG has played an essential role. In this talk, we review two important matrix optimization problems of
Correlation and Euclidean distance matrices. We reveal their striking similarities between them and we also emphasize
their distinguishing features. We will pay a particular attention to the key problem structures that render the semi-smooth
Newton-CG an efficient method for them. We then demonstrate a few of important applications, including the spherical
embedding of high-dimensional data. This talk is based on the research with a number of collaborators over the past few
years.
报告人简介:
EDUCATION
1996 PhD in Operational Research, Chinese Academy of Science, Beijing, China.
1993 MSc in Operational Research, Qufu Normal University, China.
1990 BSc in Probability and Statistics, Peking University, China
EMPLOYMENT
2010--present. Associate professor in Operational Research, School of Mathematical Sciences,University of Southampton, UK.
2004 --2009. Lecturer and then Senior Lecturer in Operational Research, School of MathematicalSciences, University of Southampton, UK.
PROFESSIONAL ASSOCIATIONS
Associate Editor of Asia-Pacific Journal of Operational Research
Associate Editor of Mathematical Programming Computation
