Positively Weighted Kernel Quadrature via Subsampling

Neural Information Processing Systems 

We study kernel quadrature rules with convex weights. Our approach combines the spectral properties of the kernel with recombination results about point measures. This results in effective algorithms that construct convex quadrature rules using only access to i.i.d.

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