IKA: Independent Kernel Approximator
2018-09-05Code Available0· sign in to hype
Matteo Ronchetti
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- gitlab.com/matteo-ronchetti/IKAOfficialIn papernone★ 0
Abstract
This paper describes a new method for low rank kernel approximation called IKA. The main advantage of IKA is that it produces a function (x) defined as a linear combination of arbitrarily chosen functions. In contrast the approximation produced by Nystr\"om method is a linear combination of kernel evaluations. The proposed method consistently outperformed Nystr\"om method in a comparison on the STL-10 dataset. Numerical results are reproducible using the source code available at https://gitlab.com/matteo-ronchetti/IKA