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