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A related task is opting for examples to possess quoting integrals using Bayesian quadrature. We reveal that the new standards reduced when choosing products within the kernel herding is the same as the brand new rear variance in the Bayesian quadrature. I then demonstrate that sequential Bayesian quadrature can be considered a weighted type of kernel herding and this hits performance a lot better than any adjusted herding approach.
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