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Communication Dans Un Congrès Année : 2019

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

Résumé

This paper focuses on Monte Carlo integration with determinantal point processes (DPPs) which enforce negative dependence between quadrature nodes. We survey the properties of two unbiased Monte Carlo estimators of the integral of interest: a direct one proposed by Bardenet & Hardy (2016) and a less obvious 60-year-old estimator by Ermakov & Zolotukhin (1960) that actually also relies on DPPs. We provide an efficient implementation to sample exactly a particular multidimen-sional DPP called multivariate Jacobi ensemble. This let us investigate the behavior of both estima-tors on toy problems in yet unexplored regimes.
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Dates et versions

hal-02160382 , version 1 (19-06-2019)

Identifiants

  • HAL Id : hal-02160382 , version 1

Citer

Guillaume Gautier, R. Bardenet, Michal Valko. On two ways to use determinantal point processes for Monte Carlo integration. NEGDEPML 2019 - ICML Workshop on Negative Dependence in ML, Jun 2019, Long Beach, CA, United States. ⟨hal-02160382⟩
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