Vector-valued Reproducing Kernel Banach Spaces with Applications to Multi-task Learning

Haizhang Zhang; Jun Zhang

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arXiv · 1111.1037

Vector-valued Reproducing Kernel Banach Spaces with Applications to Multi-task Learning

Haizhang Zhang·Jun Zhang

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Abstract

Motivated by multi-task machine learning with Banach spaces, we propose the notion of vector-valued reproducing kernel Banach spaces (RKBS). Basic properties of the spaces and the associated reproducing kernels are investigated. We also present feature map constructions and several concrete examples of vector-valued RKBS. The theory is then applied to multi-task machine learning. Especially, the representer theorem and characterization equations for the minimizer of regularized learning schemes in vector-valued RKBS are established.

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BibTeX RIS

Haizhang Zhang, Jun Zhang. 2011-11-04. Vector-valued Reproducing Kernel Banach Spaces with Applications to Multi-task Learning. https://arxiv.org/abs/1111.1037

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