1 citations · 1 across the 4 of their papers we have counts for
4 papers
Random-prime--fixed-vector randomised lattice-based algorithm for high-dimensional integration
Frances Y. Kuo, Dirk Nuyens, Laurence Wilkes
We show that a very simple randomised algorithm for numerical integration can produce a near optimal rate of convergence for integrals of functions in the -dimensional weighted…
Comparison of Two Search Criteria for Lattice-based Kernel Approximation
Frances Y. Kuo, Weiwen Mo, Dirk Nuyens +2
The kernel interpolant in a reproducing kernel Hilbert space is optimal in the worst-case sense among all approximations of a function using the same set of function values. In thi…
Constructing Embedded Lattice-based Algorithms for Multivariate Function Approximation with a Composite Number of Points
Frances Y. Kuo, Weiwen Mo, Dirk Nuyens
We approximate -variate periodic functions in weighted Korobov spaces with general weight parameters using function values at lattice points. We do not limit to be a pri…
Preintegration is not smoothing when monotonicity fails
Alexander D. Gilbert, Frances Y. Kuo, Ian H. Sloan
Preintegration is a technique for high-dimensional integration over -dimensional Euclidean space, which is designed to reduce an integral whose integrand contains kinks or jumps…