These deterministic multi-level algorithms use variable subspace sampling and they are superior to any deterministic algorithm based on fixed subspace sampling.

Aug 26, 2010 · This article is part of a recent line of research on infinite-dimensional quadrature problems, where the cost of function evaluation is assumed ...

Mar 12, 2010 · This motivates the construction and the analysis of algorithms for numerical integration with respect to a product probability measure on the ...

These deter- ministic multi-level algorithms use variable subspace sampling and they are superior to any deterministic algorithm based on fixed subspace ...

These deterministic multi-level algorithms use variable subspace sampling and they are superior to any deterministic algorithm based on fixed subspace sampling ...

we obtain new algorithms for infinite-dimensional integration. These deterministic multi-level algorithms use variable subspace sampling and they are ...

We combine tractability results for finite-dimensional integration with the multi-level technique to construct new algorithms for infinite-dimensional ...

This paper presents new randomized multilevel algorithms to tackle the infinite-dimensional integration problem on weighted reproducing kernel Hilbert ...

Abstract. We study randomized algorithms for numerical integration with respect to a product probability measure on the sequence space RN.

In this paper we present error and performance analysis of a Monte Carlo variance reduction method for solving multidimensional integrals and integral equations ...