学术报告(徐洪坤教授,2019.11.26)

作者: 时间:2019-11-21 点击数:

学术报告(2019091

 

报告题目: 无限维空间中的投影次梯度方法(Projected Subgradient Methods in Infinite Dimensional Spaces)

报告人:徐洪坤教授(杭州电子科技大学)

报告时间20191126日(周二),上午0930-12:00

报告地点:理科实验楼314报告厅

 

报告摘要(Abstract):

Subgradient methods, introduced by Shor and developed by Albert, Iusem, Nesterov, Polyak, Soloov, and many others, are used to solve nondifferentiable optimization problems. The major differences from the gradient descent methods (or projection-gradient methods) for differentiable optimization problems lie in the selection manners of the step-sizes. For instance, constant step-sizes for differentiable objective functions no longer work for nondifferentiable objective functions; for the latter case, diminishing step-sizes must however be adopted.

In this talk, we will first review some existing projected subgradient methods and the main purpose is to discuss weak and strong convergence of projected subgradient methods in an infinite-dimensional Hilbert space. Some novel approaches for strong convergence analysis of projected subgradient methods will particularly be presented.

 

报告人简介: 徐洪坤,杭州电子科技大学教授、博士生导师。徐洪坤教授是发展中国家科学院院士、南非科学院院士,担任20多种数学杂志编委,50余次国际学术会议邀请和主旨报告。2014-2016年入选汤森路透全球《高被引学者》,2014年入选浙江省千人计划2017年入选科睿唯安全球《高被引学者》。已发表论文200余篇,主要研究兴趣包括:非线性泛函分析、最优化理论和算法、巴拿赫空间几何理论,非线性映像迭代方法,反问题及其正则化方法,金融数学等。

 

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