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Related papers: On approximation by tight wavelet frames on Vilenk…

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Consider $G=\SL_{ d }(\mathbb R)$ and $ \Gamma=\SL_{ d }(\mathbb Z)$. It was recently shown by the second-named author \cite{s} that for some diagonal subgroups $\{g_t\}\subset G$ and unipotent subgroups $U\subset G$, $g_t$-trajectories of…

Dynamical Systems · Mathematics 2015-06-01 Dmitry Kleinbock , Ronggang Shi , Barak Weiss

The constrained mock-Chebyshev least squares operator is a linear approximation operator based on an equispaced grid of points. Like other polynomial or rational approximation methods, it was recently introduced in order to defeat the Runge…

Numerical Analysis · Mathematics 2022-09-21 Francesco Dell'Accio , Federico Nudo

We study Min-Max affine approximants of a continuous convex or concave function $f:\Delta\subset \mathbb R^k\xrightarrow{} \mathbb R$ where $\Delta$ is a convex compact subset of $\mathbb R^k$. In the case when $\Delta$ is a simplex we…

Optimization and Control · Mathematics 2021-08-19 Steven B. Damelin , David L. Ragozin , Michael Werman

Random feature approximation is arguably one of the most popular techniques to speed up kernel methods in large scale algorithms and provides a theoretical approach to the analysis of deep neural networks. We analyze generalization…

Machine Learning · Computer Science 2023-08-30 Mike Nguyen , Nicole Mücke

In this paper we study greedy approximation in Banach spaces. We discuss a modification of the Weak Chebyshev Greedy Algorithm, in which steps of the algorithm can be executed imprecisely. Such inaccuracies are represented by both absolute…

Functional Analysis · Mathematics 2021-06-07 Anton Dereventsov

Low-rank approximations of large kernel matrices are ubiquitous in machine learning, particularly for scaling Gaussian Processes to massive datasets. The Pivoted Cholesky decomposition is a standard tool for this task, offering a…

Machine Learning · Computer Science 2026-01-21 Gil Shabat

We study high-dimensional nonlinear approximation of functions in H\"older-Nikol'skii spaces $H^\alpha_\infty(\mathbb{I}^d)$ on the unit cube $\mathbb{I}^d:=[0,1]^d$ having mixed smoothness, by parametric manifolds. The approximation error…

Numerical Analysis · Mathematics 2021-02-09 Dinh Dũng , Van Kien Nguyen

We investigate the strong convergence properties of a proximal-gradient inertial algorithm with two Tikhonov regularization terms in connection to the minimization problem of the sum of a convex lower semi-continuous function $f$ and a…

Optimization and Control · Mathematics 2024-07-16 Szilárd Csaba László

We investigate the approximation of $d$-variate periodic functions in Sobolev spaces of dominating mixed (fractional) smoothness $s>0$ on the $d$-dimensional torus, where the approximation error is measured in the $L_2-$norm. In other…

Numerical Analysis · Mathematics 2013-12-24 Thomas Kuehn , Winfried Sickel , Tino Ullrich

Wavelet frames for $L^2({\mathbb R})$ can be characterized by means of spectral techniques. This work uses spectral formulas to determine all the tight wavelet frames for $L^2({\mathbb R})$ with a fixed finite number of generators of…

Functional Analysis · Mathematics 2019-01-24 F. Gómez-Cubillo , S. Villullas

We study the approximation of functions that map a Euclidean domain $\Omega\subset \mathbb{R}^{d}$ into an $n$-dimensional Riemannian manifold $(M,g)$ minimizing an elliptic, semilinear energy in a function set $H\subset W^{1,2}(\Omega,M)$.…

Numerical Analysis · Mathematics 2018-05-25 Hanne Hardering

We characterize the lack of compactness in the critical embedding of functions spaces $X\subset Y$ having similar scaling properties in the following terms : a sequence $(u_n)_{n\geq 0}$ bounded in $X$ has a subsequence that can be…

Functional Analysis · Mathematics 2012-07-17 Hajer Bahouri , Albert Cohen , Gabriel Koch

We investigate the strong and the weak convergence properties of the following gradient projection algorithm with Tikhonov regularizing term \[ x_{n+1}=P_{Q}(x_{n}-\gamma_{n}\nabla f(x_{n})-\gamma_{n}\alpha_{n}\nabla \phi (x_{n})), \] where…

Optimization and Control · Mathematics 2019-10-18 Ramzi May

In this work, we study groupoids and their approximation properties, generalizing both the definitions and some known results for the group case. More precisely, we introduce weak amenability for groupoids using the definition of the…

Operator Algebras · Mathematics 2025-03-21 Tomás Pacheco

We prove a sharp analogue of Minkowski's inhomogeneous approximation theorem over fields of power series $\mathbb{F}_q((T^{-1}))$. Furthermore, we study the approximation to a given point $\underline{y}$ in $\mathbb{F}_q((T^{-1}))^2$ by the…

Number Theory · Mathematics 2020-09-07 Yann Bugeaud , L. Singhal , Zhenliang Zhang

This research includes the study of some positive sampling Kantorovich operators (SK operators) and their convergence properties. A comprehensive analysis of both local and global approximation properties is presented using sampling…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Digvijay Singh , Rahul Shukla , Karunesh Kumar Singh

We consider $\mathbb{L}_2$-approximation of elements of a Hermite space of analytic functions over $\mathbb{R}^s$. The Hermite space is a weighted reproducing kernel Hilbert space of real valued functions for which the Hermite coefficients…

Numerical Analysis · Mathematics 2015-10-09 Christian Irrgeher , Peter Kritzer , Friedrich Pillichshammer , Henryk Wozniakowski

We study spaces $\mathcal{CV}^{k}(\Omega,E)$ of $k$-times continuously partially differentiable functions on an open set $\Omega\subset\mathbb{R}^{d}$ with values in a locally convex Hausdorff space $E$. The space…

Functional Analysis · Mathematics 2020-02-05 Karsten Kruse

Following the development of weighted asymptotic approximation properties of matrices, we introduce the analogous uniform approximation properties (that is, study the improvability of Dirichlet's Theorem). An added feature is the use of…

Number Theory · Mathematics 2022-02-25 Dmitry Kleinbock , Anurag Rao

Given a positive integer $p$, we consider $W^{1,p}$-maps from a Euclidean domain of dimension $p+1$ into a closed Riemannian manifold $\mathcal{N}$. The target manifold is required to satisfy suitable topological conditions; in particular,…

Functional Analysis · Mathematics 2026-05-28 Giacomo Canevari , Giandomenico Orlandi
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