Zobrazeno 1 - 10
of 426
pro vyhledávání: '"Dung Dinh"'
Publikováno v:
Tạp chí Khoa học Đại học Cần Thơ, Vol 59, Iss 2 (2023)
Giáo dục dinh dưỡng cho công dân nói chung và học sinh tiểu học nói riêng là vấn đề cấp thiết, được các nhà lãnh đạo, các nhà nghiên cứu và các nhà giáo dục quan tâm. Trong chương trình giáo dục
Externí odkaz:
https://doaj.org/article/e00207fbeaff4fc7aa982545092511a6
Autor:
Dũng, Dinh
We propose novel methods for approximate sampling recovery and integration of functions in the Freud-weighted Sobolev space $W^r_{p,w}(\mathbb{R})$ with the approximation error measured in the norm of the Freud-weighted Lebesgue space $L_{q,w}(\mathb
Externí odkaz:
http://arxiv.org/abs/2501.01167
Autor:
Bartel, Felix, Dũng, Dinh
We proved convergence rates of linear sampling recovery of functions in an abstract Bochner space satisfying some weighted $\ell_2$-summability of their generalized polynomial chaos expansion coefficients, by extended least squares methods. As applic
Externí odkaz:
http://arxiv.org/abs/2409.05050
Autor:
Dũng, Dinh
We study linear polynomial approximation of functions in weighted Sobolev spaces $W^r_{p,w}(\mathbb{R}^d)$ of mixed smoothness $r \in \mathbb{N}$, and their optimality in terms of Kolmogorov and linear $n$-widths of the unit ball $\boldsymbol{W}^r_{p
Externí odkaz:
http://arxiv.org/abs/2407.19442
Autor:
Dũng, Dinh
We study sparse-grid linear sampling algorithms and their optimality for approximate recovery of functions with mixed smoothness on $\mathbb{R}^d$ from a set of $n$ their sampled values in two different settings: (i) functions to be recovered are in
Externí odkaz:
http://arxiv.org/abs/2405.16400
Autor:
Dũng, Dinh
We give a short survey of recent results on sparse-grid linear algorithms of approximate recovery and integration of functions possessing a unweighted or weighted Sobolev mixed smoothness based on their sampled values at a certain finite set. Some of
Externí odkaz:
http://arxiv.org/abs/2309.04994
Autor:
Dũng, Dinh
We investigate the approximation of weighted integrals over $\mathbb{R}^d$ for integrands from weighted Sobolev spaces of mixed smoothness. We prove upper and lower bounds of the convergence rate of optimal quadratures with respect to $n$ integration
Externí odkaz:
http://arxiv.org/abs/2208.09108
Autor:
Dũng, Dinh, Nguyen, Van Kien
We investigate the numerical approximation of integrals over $\mathbb{R}^d$ equipped with the standard Gaussian measure $\gamma$ for integrands belonging to the Gaussian-weighted Sobolev spaces $W^\alpha_p(\mathbb{R}^d, \gamma)$ of mixed smoothness $
Externí odkaz:
http://arxiv.org/abs/2207.01155
We establish sparsity and summability results for coefficient sequences of Wiener-Hermite polynomial chaos expansions of countably-parametric solutions of linear elliptic and parabolic divergence-form partial differential equations with Gaussian rand
Externí odkaz:
http://arxiv.org/abs/2201.01912
Autor:
Dũng, Dinh
We obtained convergence rates of the collocation approximation by deep ReLU neural networks of solutions to elliptic PDEs with lognormal inputs, parametrized by $\boldsymbol{y}$ from the non-compact set $\mathbb{R}^\infty$. The approximation error is
Externí odkaz:
http://arxiv.org/abs/2111.05504