林荣荣老师受邀进行讲座

发布时间: 2021-08-08 09:19:00

题      目：Multi task Learning in Vector valued Reproducing Kernel Banach Spaces with the l1 Norm

报 告 人：林荣荣讲师    广东工业大学

时      间：2021-08-07 16:00--17:00

地      点：一课东201

报告人简介:

       林荣荣老师于2017年6月在中山大学数学学院取得博士学位。博士期间作为科研助理曾访问加拿大阿尔伯特大学一年。现任广东工业大学讲师，已在机器学习核函数方法和时频分析研究领域发表多篇论文。

摘      要：

       Targeting at sparse multi-task learning, we consider regularization models with an l1 penalty on the coefficients of kernel functions. In order to provide a kernel method for this model, we construct a class of vector-valued reproducing kernel Banach spaces with the l1 norm. The notion of multi-task admissible kernels is proposed so that the constructed spaces could have desirable properties including the crucial linear representer theorem. Such kernels are related to bounded Lebesgue constants of a kernel interpolation question. We study the Lebesgue constant of multi-task kernels and provide examples of admissible kernels. This is a joint work with Prof. Guohui Song (ODU) and Haizhang Zhang (SYSU).