Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling.
CoRR(2023)
摘要
In this work we consider the problem of numerical integration, i.e.,
approximating integrals with respect to a target probability measure using only
pointwise evaluations of the integrand. We focus on the setting in which the
target distribution is only accessible through a set of $n$ i.i.d.
observations, and the integrand belongs to a reproducing kernel Hilbert space.
We propose an efficient procedure which exploits a small i.i.d. random subset
of $m更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要