学术报告:Sparse Machine Learning in a Banach Space

编辑:    发布时间:2020-10-13    次点击

主讲人:许跃生(Yuesheng Xu),美国Old Dominion University

时间: 北京时间10月19日(周一)上午8:30-9:30

地点:ZOOM云会议(请安装Zoom后,点击下方链接) 

https://odu.zoom.us/j/7435181691

Meeting ID: 743 518 1691


联系人:张 娜   副教授

联系电话:15914386597

欢迎广大师生积极参加!


摘 要:We will report in this talk recent development of kernel based machine learning. We will first review a basic classical problem in machine learning - classification, from which we introduce kernel based machine learning methods. We will consider two fundamental problems in kernel based machine learning: representer theorems and kernel universality. We will then elaborate recent exciting advances in sparse learning. In particular, we will discuss the notion of reproducing kernel Banach spaces and learning in a Banach space.


报告人简介:

许跃生教授现任美国奥多明尼昂大学教授,曾任美国西弗吉尼亚大学Eberly讲席教授,雪城大学终身教授,中山大学国华讲席教授。现担任多个学术期刊编委。论文发表在Applied and Harmonic Computational Analysis, SIAM Journal on Numerical Analysis, Inverse Problems, SIAM Journal on Imaging Science, IEEE Transactions on Medical Imaging等国际著名期刊,共计一百八十余篇。 


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