9 citations · 22 across the 6 of their papers we have counts for
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math.NA2017
Geometry-Oblivious FMM for Compressing Dense SPD Matrices
Chenhan D. Yu, James Levitt, Severin Reiz +1
We present GOFMM (geometry-oblivious FMM), a novel method that creates a hierarchical low-rank approximation, "compression," of an arbitrary dense symmetric positive definite (SPD)…
cs.DC2017★ 2 cited
An Parallel Fast Direct Solver for Kernel Matrices
Chenhan D. Yu, William B. March, George Biros
Kernel matrices appear in machine learning and non-parametric statistics. Given points in dimensions and a kernel function that requires work to evaluate,…