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Fast Kernel Summation.pdf

3539-fast-high-dimensional-kernel-summations-using-the-monte-carlo-multipole-method.pdf
Preview of Fast Kernel Summation
🔗 Source: papers.nips.cc
📊 Size: 132 KB
👤 Author: Dongryeol Lee, Alexander G. Gray
⬇️ Downloads: 75

Summary

A new fast Gaussian summation algorithm for high-dimensional datasets is proposed, utilizing probabilistic relative error bounds and a new tree structure called subspace tree to reduce the computational cost of each distance computation. The algorithm guarantees probabilistic relative error on each kernel sum and can be applied to high-dimensional Gaussian summations, providing empirical speedup results on low to high-dimensional datasets up to 89 dimensions.

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Description

A new fast Gaussian summation algorithm for high-dimensional datasets is proposed, utilizing probabilistic relative error bounds and a new tree structure...

Technical Information

  • File Format: PDF
  • File Size: 132 KB
  • Pages: 8
  • Language: EN
  • Author: Dongryeol Lee, Alexander G. Gray
  • Total Downloads: 75
  • Last Updated: 6 days ago

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