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Nov 9, 2011 · We present a kernel classification approach based on the Nyström method and derive its generalization performance using the improved bound.
Jun 27, 2013 · We present a kernel classification approach based on the Nyström method and derive its generalization performance using the improved bound.
We present a kernel classification approach based on the Nyström method and derive its generalization performance using the improved bound. We show that ...
We present a kernel classification approach based on the Nystr\"{o}m method and derive its generalization performance using the improved bound. We show that ...
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A kernel classification approach based on the Nyström method is presented and it is shown that when the eigenvalues of the kernel matrix follow a p-power ...
We present a kernel classification approach based on the Nystr\"{o}m method and derive its generalization performance using the improved bound. We show that ...
We develop three approaches for analyzing the approximation bound for the Nystrom method, one based on the matrix perturbation theory, one based on the ...
We reconsider randomized algorithms for the low-rank approximation of SPSD matrices such as Laplacian and kernel matrices that arise in data analysis and.
We develop an improved bound for the ap- proximation error of the Nyström method under the assumption that there is a large eigengap in the spectrum of kernel ...
Missing: Classification | Show results with:Classification
Low-rank matrix approximation is an effective tool in alleviating the memory and computa- tional burdens of kernel methods and sampling, as the mainstream of ...