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學術報告(徐洪坤教授,2019.11.26)

作者: 时间:2019-11-21 点击数:

學術報告(2019091

 

報告題目: 無限維空間中的投影次梯度方法(Projected Subgradient Methods in Infinite Dimensional Spaces)

報告人:徐洪坤教授(杭州電子科技大學)

報告時間20191126日(周二),上午0930-12:00

報告地點:理科實驗樓314報告廳

 

報告摘要(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.

 

報告人簡介: 徐洪坤,杭州電子科技大學教授、博士生導師。徐洪坤教授是發展中國家科學院院士、南非科學院院士,擔任20多種數學雜志編委,50余次國際學術會議邀請和主旨報告。2014-2016年入選湯森路透全球《高被引學者》,2014年入選浙江省千人計劃2017年入選科睿唯安全球《高被引學者》。已發表論文200余篇,主要研究興趣包括:非線性泛函分析、最優化理論和算法、巴拿赫空間幾何理論,非線性映像叠代方法,反問題及其正則化方法,金融數學等。

 

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