8 citations · 15 across the 8 of their papers we have counts for
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math.NA2018
Optimal confidence for Monte Carlo integration of smooth functions
Robert J. Kunsch, Daniel Rudolf
We study the complexity of approximating integrals of smooth functions at absolute precision with confidence level . The optimal error rate for mu…
math.NA2018★ 1 cited
Solvable Integration Problems and Optimal Sample Size Selection
Robert J. Kunsch, Erich Novak, Daniel Rudolf
We compute the integral of a function or the expectation of a random variable with minimal cost and use, for our new algorithm and for upper bounds of the complexity, i.i.d. sample…
math.NA2018
The Difficulty of Monte Carlo Approximation of Multivariate Monotone Functions
Robert J. Kunsch
We study the -approximation of -variate monotone functions based on information from function evaluations. It is known that this problem suffers from the curse of dimen…