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This paper discusses the dimensions of the spline spaces over T-meshes with lower degree. Two new concepts are proposed: extension of T-meshes and spline spaces with homogeneous boundary conditions. In the dimension analysis, the key…

Numerical Analysis · Mathematics 2008-04-17 Jiansong Deng , Falai Chen , Liangbing Jin

In this paper, we investigate $C^2$ super-smoothness of the full $C^1$ cubic spline space on a Powell-Sabin refined triangulation, for which a B-spline basis can be constructed. Blossoming is used to identify the $C^2$ smoothness conditions…

Numerical Analysis · Mathematics 2024-11-11 Jan Grošelj , Hendrik Speleers

We present a nodal interpolation method to approximate a subdivision model. The main application is to model and represent curved geometry without gaps and preserving the required simulation intent. Accordingly, we devise the technique to…

Computational Engineering, Finance, and Science · Computer Science 2022-11-30 Albert Jiménez-Ramos , Abel Gargallo-Peiró , Xevi Roca

We examine the necessity of interpolation in overparameterized models, that is, when achieving optimal predictive risk in machine learning problems requires (nearly) interpolating the training data. In particular, we consider simple…

Machine Learning · Statistics 2022-06-17 Chen Cheng , John Duchi , Rohith Kuditipudi

The paper suggests a method of extrapolation of notion of one-sided semi-infinite sequences representing traces of two-sided band-limited sequences; this features ensure uniqueness of this extrapolation and possibility to use this for…

Optimization and Control · Mathematics 2018-02-08 Nikolai Dokuchaev

Models with fewer parameters are often easier to interpret and more robust. Parsimony can be achieved through optimizing objectives like the AIC or BIC, which are functions of the the number of free parameters in the model. Optimizing this…

Methodology · Statistics 2026-04-21 Mateen R Shaikh

Splines and subdivision curves are flexible tools in the design and manipulation of curves in Euclidean space. In this paper we study generalizations of interpolating splines and subdivision schemes to the Riemannian manifold of shell…

Numerical Analysis · Mathematics 2017-02-23 Pascal Huber , Ricardo Perl , Martin Rumpf

Almost sure bounds are established on the uniform error of smoothing spline estimators in nonparametric regression with random designs. Some results of Einmahl and Mason (2005) are used to derive uniform error bounds for the approximation…

Statistics Theory · Mathematics 2007-06-13 P. P. B. Eggermont , V. N. LaRiccia

We study the local approximation properties in hierarchical spline spaces through multiscale quasi-interpolation operators. This construction suggests the analysis of a subspace of the classical hierarchical spline space (Vuong et al.,…

Numerical Analysis · Mathematics 2015-07-24 Annalisa Buffa , Eduardo M. Garau

While interpolatory bases such as the Lagrange basis form the cornerstone of classical finite element methods, they have been replaced in the more general finite element setting of isogeometric analysis in favor of other desirable…

Numerical Analysis · Mathematics 2025-12-09 Yannis Voet , Espen Sande

Polynomial meshes (called sometimes "norming sets") allow us to estimate the supremum norm of polynomials on a fixed compact set by the norm on its discrete subset. We give a general construction of polynomial weakly admissible meshes on…

Numerical Analysis · Mathematics 2025-01-22 Leokadia Bialas-Ciez , Agnieszka Kowalska , Alvise Sommariva

Data sites selected from modeling high-dimensional problems often appear scattered in non-paternalistic ways. Except for sporadic clustering at some spots, they become relatively far apart as the dimension of the ambient space grows. These…

Numerical Analysis · Mathematics 2021-09-28 Shao-Bo Lin , Xiangyu Chang , Xingping Sun

The simplest way to obtain continuous interpolation between two points in high dimensional space is to draw a line between them. While previous works focused on the general connectivity between model parameters, we explored linear…

Computation and Language · Computer Science 2022-11-23 Mark Rofin , Nikita Balagansky , Daniil Gavrilov

We provide a comprehensive study of interrelations between different measures of smoothness of functions on various domains and smoothness properties of approximation processes. Two general approaches to this problem have been developed:…

Classical Analysis and ODEs · Mathematics 2020-03-18 Yu. Kolomoitsev , S. Tikhonov

In some real world applications, such as spectrometry, functional models achieve better predictive performances if they work on the derivatives of order m of their inputs rather than on the original functions. As a consequence, the use of…

Statistics Theory · Mathematics 2011-05-04 Fabrice Rossi , Nathalie Villa-Vialaneix

In CAGD the design of a surface that interpolates an arbitrary quadrilateral mesh is definitely a challenging task. The basic requirement is to satisfy both criteria concerning the regularity of the surface and aesthetic concepts. With…

Numerical Analysis · Mathematics 2016-01-08 Michele Antonelli , Carolina Vittoria Beccari , Giulio Casciola

The phenomenon, known as "supersmoothness" was first observed for bivariate splines and attributed to the polynomial nature of splines. Using only standard tools from multivatiate calculus, we show that if we continuously glue two smooth…

Numerical Analysis · Mathematics 2013-02-21 Boris Shekhtman , Tatyana Sorokina

We study the smoothness properties of a global and nonautonomous topological conjugacy between a linear system and a quasilinear perturbation. The linear system exhibits a nonuniform exponential dichotomy with a nontrivial projector and…

Dynamical Systems · Mathematics 2025-01-28 Álvaro Castañeda , Ignacio Huerta , Gonzalo Robledo

There are many uses for linear fitting; the context here is interpolation and denoising of data, as when you have calibration data and you want to fit a smooth, flexible function to those data. Or you want to fit a flexible function to…

Data Analysis, Statistics and Probability · Physics 2021-09-22 David W. Hogg , Soledad Villar

It is often possible to perform reduced order modelling by specifying linear subspace which accurately captures the dynamics of the system. This approach becomes especially appealing when linear subspace explicitly depends on parameters of…

Machine Learning · Computer Science 2026-04-17 Vladimir Fanaskov , Vladislav Trifonov , Alexander Rudikov , Ekaterina Muravleva , Ivan Oseledets