Random sampling for estimating the performance of fast summations
Random sampling for estimating the performance of fast summations
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Date
2010-10-18
Authors
Srinivasan, Balaji Vasan
Duraiswami, Ramani
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Abstract
Summation of functions of N source points evaluated at M target points
occurs commonly in many applications. To scale these approaches for large
datasets, many fast algorithms have been proposed. In this technical report, we
propose a Chernoff bound based efficient approach to test the performance of a
fast summation algorithms providing a probabilistic accuracy. We further
validate and use our approach in separate comparisons.