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Robert J. Kunsch
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2020 – today
- 2024
- [j8]Robert J. Kunsch, Erich Novak, Marcin Wnuk:
Randomized approximation of summable sequences - adaptive and non-adaptive. J. Approx. Theory 304: 106056 (2024) - [j7]Robert J. Kunsch:
Linear Monte Carlo quadrature with optimal confidence intervals. J. Complex. 83: 101851 (2024) - 2023
- [i3]Robert J. Kunsch, Erich Novak, Marcin Wnuk:
Randomized approximation of summable sequences - adaptive and non-adaptive. CoRR abs/2308.01705 (2023) - [i2]Robert J. Kunsch:
Linear Monte Carlo quadrature with optimal confidence intervals. CoRR abs/2309.09059 (2023) - 2020
- [j6]Aicke Hinrichs, David Krieg
, Robert J. Kunsch
, Daniel Rudolf:
Expected dispersion of uniformly distributed points. J. Complex. 61: 101483 (2020)
2010 – 2019
- 2019
- [j5]Robert J. Kunsch
, Daniel Rudolf:
Optimal confidence for Monte Carlo integration of smooth functions. Adv. Comput. Math. 45(5): 3095-3122 (2019) - [j4]Robert J. Kunsch
:
The difficulty of Monte Carlo approximation of multivariate monotone functions. J. Approx. Theory 241: 33-56 (2019) - [j3]Robert J. Kunsch
, Erich Novak, Daniel Rudolf:
Solvable integration problems and optimal sample size selection. J. Complex. 53: 40-67 (2019) - [i1]Aicke Hinrichs, David Krieg, Robert J. Kunsch, Daniel Rudolf:
Expected dispersion of uniformly distributed points. CoRR abs/1911.12074 (2019) - 2018
- [j2]Glenn Byrenheid
, Robert J. Kunsch
, Van Kien Nguyen:
Monte Carlo methods for uniform approximation on periodic Sobolev spaces with mixed smoothness. J. Complex. 46: 90-102 (2018) - [j1]Robert J. Kunsch
:
Breaking the curse for uniform approximation in Hilbert spaces via Monte Carlo methods. J. Complex. 48: 15-35 (2018) - 2014
- [c1]Robert J. Kunsch
:
Bernstein Numbers and Lower Bounds for the Monte Carlo Error. MCQMC 2014: 471-488
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last updated on 2024-08-10 00:25 CEST by the dblp team
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