M³C replaces the hard hyperparameter optimization with a sequence of simpler problems using a majorant for the log-determinant approximated via Monte Carlo, with proven high-probability convergence to a critical point under assumptions.
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A simple MPI-based scheme for distributed uniform-tree FMMs achieves weak scaling to 3.2e10 points on 512 nodes while preserving shared-memory optimizations.
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A Majorization-Minimization with Monte Carlo Approach for Hyperparameter Estimation
M³C replaces the hard hyperparameter optimization with a sequence of simpler problems using a majorant for the log-determinant approximated via Monte Carlo, with proven high-probability convergence to a critical point under assumptions.
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A Simple Communication Scheme for Distributed Fast Multipole Methods
A simple MPI-based scheme for distributed uniform-tree FMMs achieves weak scaling to 3.2e10 points on 512 nodes while preserving shared-memory optimizations.