Geodesic
Probabilistic approach to analysis of information complexity of concret multivariate approximation problem
Zapiski Nauchnykh Seminarov POMI, Probability and statistics. Part 36, Tome 535 (2024), pp. 150-172

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Information complexity in the worst-case setting of multivariate approximation problem of functions from reproducing kernel Hilbert space with Gaussian kernel is considered. In the paper we obtain an upper estimate of information complexity for arbitrary error threshold and parametric dimension via probabilistic methods. The main result refines the logarithmic asymptotics of Khartov and Limar and complements the estimates by Fasshauer, Hickernell, and Woźniakowski. 
@article{ZNSL_2024_535_a10,
     author = {I. A. Limar},
     title = {Probabilistic approach to analysis of information complexity of concret multivariate approximation problem},
     journal = {Zapiski Nauchnykh Seminarov POMI},
     pages = {150--172},
     publisher = {mathdoc},
     volume = {535},
     year = {2024},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/ZNSL_2024_535_a10/}
}
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I. A. Limar. Probabilistic approach to analysis of information complexity of concret multivariate approximation problem. Zapiski Nauchnykh Seminarov POMI, Probability and statistics. Part 36, Tome 535 (2024), pp. 150-172. http://geodesic.mathdoc.fr/item/ZNSL_2024_535_a10/