43 citations to https://www.mathnet.ru/eng/conap6
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Egor D. Kosov, “Marcinkiewicz-type discretization of L-norms under the Nikolskii-type inequality assumption”, Journal of Mathematical Analysis and Applications, 504:1 (2021), 125358
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Lutz Kämmerer, Tino Ullrich, Toni Volkmer, “Worst-case Recovery Guarantees for Least Squares Approximation Using Random Samples”, Constr Approx, 54:2 (2021), 295
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V. Temlyakov, T. Ullrich, “Bounds on Kolmogorov widths and sampling recovery for classes with small mixed smoothness”, J. Complexity, 67 (2021), 101575–19
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F. Dai, A. Prymak, A. Shadrin, V. Temlyakov, S. Tikhonov, “Sampling discretization of integral norms”, Constr. Approx., 54:3 (2021), 455–471
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Moritz Moeller, Tino Ullrich, “$L_2$-norm sampling discretization and recovery of functions from RKHS with finite trace”, Sampl. Theory Signal Process. Data Anal., 19:2 (2021)
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V. N. Temlyakov, “Sampling Discretization of Integral Norms of the Hyperbolic Cross Polynomials”, Proc. Steklov Inst. Math., 312 (2021), 270–281
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F. Dai, A. Prymak, A. Shadrin, V. Temlyakov, S. Tikhonov, “Entropy numbers and Marcinkiewicz-type discretization”, J. Funct. Anal., 281:6 (2021), 109090–25
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V. Temlyakov, “On optimal recovery in $L_2$”, J. Complexity, 65 (2021), 101545–0
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Albert Cohen, Wolfgang Dahmen, Ronald DeVore, James Nichols, “Reduced Basis Greedy Selection Using Random Training Sets”, ESAIM: M2AN, 54:5 (2020), 1509
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Vladimir Temlyakov, “Connections between numerical integration, discrepancy, dispersion, and universal discretization”, The SMAI Journal of computational mathematics, S5 (2020), 185