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Theory of Matching Pursuit in Kernel Defined Feature Spaces

Published on Feb 4, 20254864 Views

We analyse matching pursuit for kernel principal components analysis (KPCA) by proving that the sparse subspace it produces is a sample compression scheme. We show that this bound is tighter than the

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