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Accelerated decomposition of bistochastic kernel matrices by low rank approximation
We develop an accelerated algorithm for the approximate eigenvalue decomposition of symmetrically normalized kernel matrices, focusing on a bistochastic normalization. Our approach constructs a low rank approximation of the original kernel matrix by the pivoted partial Cholesky algorithm, and uses i
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