A Generalized Representer Theorem
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Summary
The result shows that a wide range of problems have optimal solutions that live in the finite dimensional span of the training examples mapped into feature space, thus enabling us to carry out kernel algorithms independent of the (potentially infinite) dimensionality of the feature space.
- Published
- 2001-07-16
- Cited by
- 1,980
- References
- 31
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:9256459
References
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- Kernel Principal Component Analysis
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