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Learning rates for multi-task regularization networks

  • Published:2021-11 Issue: Volume:466 Page:243-251
  • ISSN:0925-2312
  • Container-title:Neurocomputing
  • language:en
  • Short-container-title:Neurocomputing

Author:

Gui Jie,Zhang Haizhang

Funder

Natural Science Foundation of Guangdong Province

Guangdong Province Key Laboratory of Computational Science

National Natural Science Foundation of China

Sun Yat-sen University

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference29 articles.

1. When is there a representer theorem? Vector versus matrix regularizers;Argyriou;J. Mach. Learn. Res.,2009

2. Theory of reproducing kernels;Aronszajn;Trans. Amer. Math. Soc.,1950

3. Banach and Hilbert Spaces of Vector-valued Functions, Pitman Research Notes in Mathematics 90;Burbea,1984

4. Universal multi-task kernels;Caponnetto;J. Mach. Learn. Res.,2008

5. Vector valued reproducing kernel Hilbert spaces of integrable functions and Mercer theorem;Carmeli;Anal. Appl.,2006

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