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20200922 孙德锋 Adaptive Sieving with PPDNA for Solving Sparse Statistical Optimization Problems

发布时间: 2021-09-21 11:32    浏览次数:     来源:明升体育|官网

报告题目: Adaptive Sieving with PPDNA for Solving Sparse Statistical Optimization Problems
报告人: 孙德锋教授(香港理工大学)
报告时间: 2020年9月22 日(周二)下午 5: 00-6: 30
腾讯会议ID: 684 867 411
报告摘要:  
It is widely believed by many researchers, in particular by those outside the traditional optimization community, that the second-order methods such as Newton’s method are no longer applicable for solving large scale optimization problems. This is partially true for optimization models that neither need a good optimal solution nor need to be solved quickly.  In this talk, we shall first use large scale statistical optimization problems arising from machine learning to explain why the second-order methods, in particular the proximal point dual Newton methods (PPDNA), if wisely used, can be much faster than the first-order methods. The key point is to make use of the second order sparsity of the optimal solutions in addition to the data sparsity so that, at each iteration, the computational costs of the second order methods can be comparable or even lower than those of the first order methods. Equipped with the PPDNA, we shall then introduce adaptive sieving methodologies to generate solution paths of very large sparse statistical optimization problems of particular importance in applications. Finally, we shall illustrate the high efficiency of our approach with extensive numerical results.    

个人简历:
Professor Defeng Sun is currently Chair Professor of Applied Optimization and Operations Research at the Hong Kong Polytechnic University and serves as the President of the Hong Kong Mathematical Society.  He mainly publishes in convex and non-convex continuous optimization. Together with Professor Kim-Chuan Toh and Dr Liuqin Yang, he was awarded the triennial 2018 Beale--Orchard-Hays Prize for Excellence in Computational Mathematical Programming by the Mathematical Optimization Society. He served as editor-in-chief of Asia-Pacific Journal of Operational Research from 2011 to 2013 and he now serves as associate editor of Mathematical Programming, SIAM Journal on Optimization, Journal of the Operations Research Society of China, Journal of Computational Mathematics, and Science China: Mathematics. He was elected as a SIAM Fellow in 2020.

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