Abstract

Many applications of machine learning require development of sparse approximation and Banach space methods. Reproducing kernel Banach spaces provide a solid mathematical foundation for such purposes. We survey recent progress on the theory and construction of reproducing kernel Banach spaces. Applications of such spaces in sampling theory, machine learning and functional analysis will be introduced.

About Prof. Zhang

张海樟，中山大学珠海校区数学学院教授。研究兴趣包括学习理论、应用调和分析以及函数逼近。在国际上首创了再生核巴拿赫空间理论，以此为基础的分类方法入选剑桥大学出版社的《数学心理学新手册》。在Journal of Machine Learning Research、Applied and Computational Harmonic Analysis等发表多篇原创性工作。主持包括优秀青年基金在内的四项国家基金。