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- Representer_theorem abstract "In statistical learning theory, a representer theorem is any of several related results stating that a minimizer of a regularized empirical risk function defined over a reproducing kernel Hilbert space can be represented as a finite linear combination of kernel products evaluated on the input points in the training set data.".
- Representer_theorem wikiPageID "35887507".
- Representer_theorem wikiPageRevisionID "604026148".
- Representer_theorem hasPhotoCollection Representer_theorem.
- Representer_theorem subject Category:Computational_learning_theory.
- Representer_theorem subject Category:Hilbert_space.
- Representer_theorem subject Category:Machine_learning.
- Representer_theorem subject Category:Theoretical_computer_science.
- Representer_theorem comment "In statistical learning theory, a representer theorem is any of several related results stating that a minimizer of a regularized empirical risk function defined over a reproducing kernel Hilbert space can be represented as a finite linear combination of kernel products evaluated on the input points in the training set data.".
- Representer_theorem label "Representer theorem".
- Representer_theorem sameAs m.0jwvkm8.
- Representer_theorem sameAs Q7314263.
- Representer_theorem sameAs Q7314263.
- Representer_theorem wasDerivedFrom Representer_theorem?oldid=604026148.
- Representer_theorem isPrimaryTopicOf Representer_theorem.