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学术报告:Discrete Approximation method for Distributionally Robust Optimization

2020年12月18日 09:53  点击:[]

大连理工大学刘永朝教授学术报告

一、报告题目:Discrete Approximation method for Distributionally Robust Optimization

二、报告人:刘永朝教授—大连理工大学

三、报告时间:2020年12月20日星期日下午16:20

四、报告地点:数学与统计学院会议室80602

五、报告摘要:

Discrete approximation, which has been the prevailing scheme in stochastic programming in the past decade, has been extended to distributionally robust optimization (DRO) recently. In this talk, we conduct rigorous quantitative stability analysis of discrete approximation schemes for DRO, which measures the approximation error in terms of discretization sample size. Efficient numerical methods for specifically solving discrete approximation DRO problems with thousands of samples are also designed. In particular, we reformulate different types of discrete approximation problems into a class of saddle point problems with completely separable structures. The stochastic primal-dual hybrid gradient (PDHG) algorithm where in each iteration we update a random subset of the sampled variables is then amenable as a solution method for the reformulated saddle point problems. Some preliminary numerical tests are reported.

六、报告人简介:

刘永朝,博士,大连理工大学数学科学学院教授、博士生导师。2005年和2008年于大连海事大学数学系获得学士和硕士学位,2011年于大连理工大学数学科学学院获得博士学位, 2014年11月至2016年4月在南安普顿大学从事博士后研究。主要研究方向为随机最优化,在 Mathematical Programming, SIAM Journal on Optimization,Mathematics of Operations Research,SIAM Journal on Numerical Analysis等优化顶级期刊发表学术论文10多篇;主持国家自然科学基金3项(面上2项、青年1项)。

 

欢迎感兴趣的老师和同学参加!

 

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