[26] How many continuous measurements are needed to learn a vector?
Coauthor(s): E. Novak and M. Ullrich. Preprint.
arxiv.org/abs/2412.06468
[25] A simple universal algorithm for high-dimensional integration.
Coauthor(s): T. Goda. Preprint.
arxiv.org/abs/2411.19164
[24] On the power of adaption and randomization.
Coauthor(s): E. Novak and M. Ullrich. Preprint.
arxiv.org/abs/2406.07108
[23] Sampling projections in the uniform norm.
Coauthor(s): K. Pozharska, M. Ullrich, and T. Ullrich. Preprint.
arxiv.org/abs/2401.02220
[22] Homogeneous algorithms and solvable problems on cones.
Coauthor(s): P. Kritzer.
Appeared in: Journal of Complexity, 83:101840, 2024.
doi.org/10.1016/j.jco.2024.101840 | arxiv.org/abs/2311.15767
[21] Sampling recovery in L2 and other norms.
Coauthor(s): K. Pozharska, M. Ullrich, and T. Ullrich. Preprint.
arxiv.org/abs/2305.07539
[20] Tractability of sampling recovery on unweighted function classes.
Appeared in: Proceedings of the American Mathematical Society, Series B, 11:115-125, 2024.
doi.org/10.1090/bproc/216 | arxiv.org/abs/2304.14169
[19] New lower bounds for the integration of periodic functions.
Coauthor(s): J. Vybíral.
Appeared in: Journal of Fourier Analysis and Applications, 29:41, 2023.
doi.org/10.1007/s00041-023-10021-7 | arxiv.org/abs/2302.02639
[18] Exponential tractability of L2-approximation with function values.
Coauthor(s): P. Siedlecki, M. Ullrich, and H. Woźniakowski.
Appeared in: Advances in Computational Mathematics, 49:18, 2023.
doi.org/10.1007/s10444-023-10021-7 | arxiv.org/abs/2205.04141
[17] A sharp upper bound for sampling numbers in L2.
Coauthor(s): M. Dolbeault and M. Ullrich.
Appeared in: Applied and Computational Harmonic Analysis, 63:113-134, 2023.
doi.org/10.1016/j.acha.2022.12.001 | arxiv.org/abs/2204.12621
[16] Function recovery on manifolds using scattered data.
Coauthor(s): M. Sonnleitner.
Appeared in: Journal of Approximation Theory, 305:106098, 2025.
doi.org/10.1016/j.jat.2024.106098 | arxiv.org/abs/2109.04106
[15] Lower bounds for integration and recovery in L2.
Coauthor(s): A. Hinrichs, E. Novak, and J. Vybíral.
Appeared in: Journal of Complexity, 72:101662, 2022.
doi.org/10.1016/j.jco.2022.101662 | arxiv.org/abs/2108.11853
[14] Recovery of Sobolev functions restricted to iid sampling.
Coauthor(s): E. Novak and M. Sonnleitner.
Appeared in: Mathematics of Computation, 91:2715-2738, 2022.
doi.org/10.1090/mcom/3763 | arxiv.org/abs/2108.02055
[13] Function values are enough for L2-approximation: Part II.
Coauthor(s): M. Ullrich.
Appeared in: Journal of Complexity, 66:101569, 2021.
doi.org/10.1016/j.jco.2021.101569 | arxiv.org/abs/2011.01779
[12] Random points are optimal for the approximation of Sobolev functions.
Coauthor(s): M. Sonnleitner.
Appeared in: IMA Journal of Numerical Analysis, 44(3):1346-1371, 2023.
doi.org/10.1093/imanum/drad014 | arxiv.org/abs/2009.11275
[11] Lower bounds for the error of quadrature formulas for Hilbert spaces.
Coauthor(s): A. Hinrichs, E. Novak, and J. Vybíral.
Appeared in: Journal of Complexity, 65:101544, 2021.
doi.org/10.1016/j.jco.2020.101544 | arxiv.org/abs/2004.00274
[10] Expected dispersion of uniformly distributed points.
Coauthor(s): A. Hinrichs, R. J. Kunsch, and D. Rudolf.
Appeared in: Journal of Complexity, 61:101483, 2020.
doi.org/10.1016/j.jco.2020.101483 | arxiv.org/abs/1911.12074
[9] Function values are enough for L2-approximation.
Coauthor(s): M. Ullrich.
Appeared in: Foundations of Computational Mathematics, 21:1141-1151, 2021.
doi.org/10.1007/s10208-020-09481-w | arxiv.org/abs/1905.02516
[8] On the power of random information.
Coauthor(s): A. Hinrichs, E. Novak, J. Prochno, and M. Ullrich.
Appeared in: F. J. Hickernell, P. Kritzer (eds.): Multivariate Algorithms and Information-Based Complexity, 43-64, Berlin/Boston: DeGruyter, 2020.
doi.org/10.1515/9783110635461 | arxiv.org/abs/1903.00681
[7] Random sections of ellipsoids and the power of random information.
Coauthor(s): A. Hinrichs, E. Novak, J. Prochno, and M. Ullrich.
Appeared in: Transactions of the American Mathematical Society, 374(12):8691-8713, 2021.
doi.org/10.1090/tran/8502 | arxiv.org/abs/1901.06639
[6] Uniform recovery of high-dimensional C^r-functions.
Appeared in: Journal of Complexity, 50:116-126, 2019.
doi.org/10.1016/j.jco.2018.10.002 | arxiv.org/abs/1805.06220
[5] Recovery algorithms for high-dimensional rank one tensors.
Coauthor(s): D. Rudolf.
Appeared in: Journal of Approximation Theory, 237:17-29, 2019.
doi.org/10.1016/j.jat.2018.08.002 | arxiv.org/abs/1711.03986
[4] On the dispersion of sparse grids.
Appeared in: Journal of Complexity, 45:115-119, 2018.
doi.org/10.1016/j.jco.2017.11.005 | arxiv.org/abs/1709.02983
[3] Optimal Monte Carlo methods for L2-approximation.
Appeared in: Constructive Approximation, 49:385-403, 2019.
doi.org/10.1007/s00365-018-9428-4 | arxiv.org/abs/1705.04567
[2] Tensor power sequences and the approximation of tensor product operators.
Appeared in: Journal of Complexity, 44:30-51, 2018.
doi.org/10.1016/j.jco.2017.09.002 | arxiv.org/abs/1612.07680
[1] A universal algorithm for multivariate integration.
Coauthor(s): E. Novak.
Appeared in: Foundations of Computational Mathematics, 17:895-916, 2017.
doi.org/10.1007/s10208-016-9307-y | arxiv.org/abs/1507.06853