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ORCIDJournal of Complexity, Volume 79
Volume 79, December 2023
- Erich Novak, Friedrich Pillichshammer
:
The curse of dimensionality for the Lp-discrepancy with finite p. 101769 - Xiangyong Tan, Ling Peng, Peiwen Xiao, Qing Liu, Xiaohui Liu:
The rate of convergence for sparse and low-rank quantile trace regression. 101778 - Dinh Dung, Van Kien Nguyen, Duong Thanh Pham:
Deep ReLU neural network approximation in Bochner spaces and applications to parametric PDEs. 101779 - Alexander Kushpel:
Optimal recovery and volume estimates. 101780 - Ioannis K. Argyros, Stepan Shakhno, Samundra Regmi, Halyna Yarmola:
On the complexity of a unified convergence analysis for iterative methods. 101781 - Leszek Plaskota, Pawel Siedlecki:
Worst case tractability of linear problems in the presence of noise: Linear information. 101782 - Xia Liu:
Approximating smooth and sparse functions by deep neural networks: Optimal approximation rates and saturation. 101783 - Tong Mao, Ding-Xuan Zhou:
Rates of approximation by ReLU shallow neural networks. 101784 - Frances Y. Kuo, Dirk Nuyens, Laurence Wilkes:
Random-prime-fixed-vector randomised lattice-based algorithm for high-dimensional integration. 101785 - Thomas Jahn, Tino Ullrich, Felix Voigtländer:
Sampling numbers of smoothness classes via ℓ1-minimization. 101786
- Erich Novak:
Changes of the Editorial Board. 101792
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