An analysis of Ermakov-Zolotukhin quadrature using kernels

3 September 2023

Papers citing "An analysis of Ermakov-Zolotukhin quadrature using kernels"

11 / 11 papers shown

Title
On the design of scalable, high-precision spherical-radial Fourier features Ayoub Belhadji Qianyu Julie Zhu Youssef Marzouk 23 1 0 23 Aug 2024
A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting Masaki Adachi Satoshi Hayakawa Martin Jørgensen Saad Hamid Harald Oberhauser Michael A. Osborne GP 32 3 0 18 Apr 2024
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling Antoine Chatalic Nicolas Schreuder E. De Vito Lorenzo Rosasco 24 3 0 22 Nov 2023
Policy Gradient with Kernel Quadrature Satoshi Hayakawa Tetsuro Morimura OffRL BDL 26 0 0 23 Oct 2023
Signal reconstruction using determinantal sampling Ayoub Belhadji Rémi Bardenet P. Chainais 32 2 0 13 Oct 2023
Adaptive Batch Sizes for Active Learning A Probabilistic Numerics Approach Masaki Adachi Satoshi Hayakawa Martin Jørgensen Xingchen Wan Vu Nguyen Harald Oberhauser Michael A. Osborne 28 5 0 09 Jun 2023
Kernel quadrature with randomly pivoted Cholesky Ethan N. Epperly Elvira Moreno 24 8 0 06 Jun 2023
When can Regression-Adjusted Control Variates Help? Rare Events, Sobolev Embedding and Minimax Optimality Jose H. Blanchet Haoxuan Chen Yiping Lu Lexing Ying 41 3 0 25 May 2023
Sampling-based Nyström Approximation and Kernel Quadrature Satoshi Hayakawa Harald Oberhauser Terry Lyons 35 13 0 23 Jan 2023
Positively Weighted Kernel Quadrature via Subsampling Satoshi Hayakawa Harald Oberhauser Terry Lyons 30 24 0 20 Jul 2021
$Monte Carlo integration of non-differentiable functions on $[0,1]^ι$, $ι=1,\dots,d$, using a single determinantal point pattern defined on $[0,1]^d$$ Monte Carlo integration of non-differentiable functions on $[0,1]^ι$ , $ι=1,\dots,d$ , using a single determinantal point pattern defined on $[0,1]^d$ Jean‐François Coeurjolly Adrien Mazoyer P. Amblard 16 7 0 28 Feb 2020