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stat.ML2018
Scalable Learning in Reproducing Kernel Krein Spaces
Dino Oglic, Thomas Gärtner
We provide the first mathematically complete derivation of the Nyström method for low-rank approximation of indefinite kernels and propose an efficient method for finding an approx…
stat.ML2018
Towards A Unified Analysis of Random Fourier Features
Zhu Li, Jean-Francois Ton, Dino Oglic +1
Random Fourier features is a widely used, simple, and effective technique for scaling up kernel methods. The existing theoretical analysis of the approach, however, remains focused…