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On two ways to use determinantal point processes for Monte Carlo integration

Gautier, Guillaume et al.
arXiv (All) · Papers
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machine-learningstatistics-theory
The standard Monte Carlo estimator $\widehat{I}_N^{\mathrm{MC}}$ of $\int fdω$ relies on independent samples from $ω$ and has variance of order $1/N$. Replacing the samples with a determinantal point process (DPP), a repulsive distribution, makes the estimator consistent, with variance rates that de
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