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Multiresolution kernel matrix algebra

Published in arXiv (Cornell University) • Nov 21, 2022
NobleIDNI9P62W18R25S24
Authors:
H. Harbrecht
,
M. Multerer
,
O. Schenk

Abstract

We propose a sparse algebra for samplet compressed kernel matrices, to enable efficient scattered data analysis. We show the compression of kernel matrices by means of samplets produces optimally sparse matrices in a certain S-format. It can be performed in cost and memory that scale essentially lin...

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