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UAI
2004

On-line Prediction with Kernels and the Complexity Approximation Principle

9 years 12 months ago
On-line Prediction with Kernels and the Complexity Approximation Principle
The paper describes an application of Aggregating Algorithm to the problem of regression. It generalizes earlier results concerned with plain linear regression to kernel techniques and presents an on-line algorithm which performs nearly as well as any oblivious kernel predictor. The paper contains the derivation of an estimate on the performance of this algorithm. The estimate is then used to derive an application of the Complexity Approximation Principle to kernel methods.
Alexander Gammerman, Yuri Kalnishkan, Vladimir Vov
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where UAI
Authors Alexander Gammerman, Yuri Kalnishkan, Vladimir Vovk
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