Multiresolution Kernel Approximation for Gaussian Process Regression

نویسندگان

  • Yi Ding
  • Risi Kondor
  • Jonathan Eskreis-Winkler
چکیده

(a) (b) (c) Figure: (a) In a simple blocked low rank approximation the diagonal blocks are dense (gray), whereas the off-diagonal blocks are low rank. (b) In an HODLR matrix the low rank off-diagonal blocks form a hierarchical structure leading to a much more compact representation. (c) H2 matrices are a refinement of this idea. (a) In simple blocked low rank approximation the diagonal blocks are dens (gr y), whereas th off-diagonal blocks are low rank. (b) In an HODLR matrix the low rank off-diagonal blocks form a hierarchical structure leading to a much more compact representation. (c) H2 matrices are a refinement of this idea. Multiresolution Kernel Approximation (MKA)

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تاریخ انتشار 2017