Corpus ID: 204937125

epsilon-Samples of Kernels

@article{Phillips2011epsilonSamplesOK,
  title={epsilon-Samples of Kernels},
  author={J. M. Phillips},
  journal={arXiv: Computational Geometry},
  year={2011}
}

J. M. Phillips

Published 2011

Computer Science, Mathematics

arXiv: Computational Geometry

We study the worst case error of kernel density estimates via subset approximation. A kernel density estimate of a distribution is the convolution of that distribution with a fixed kernel (e.g. Gaussian kernel). Given a subset (i.e. a point set) of the input distribution, we can compare the kernel density estimates of the input distribution with that of the subset and bound the worst case error. If the maximum error is eps, then this subset can be thought of as an eps-sample (aka an eps… CONTINUE READING

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