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We propose a patchwise local Fourier extension method for approximating smooth functions on general two dimensional domains with curved boundaries. The domain is embedded into a Cartesian background grid and decomposed into rectangular…

Numerical Analysis · Mathematics 2026-05-12 Zhenyu Zhao , Yanfei Wang

We propose a spectral collocation method to approximate the exact boundary control of the wave equation in a square domain. The idea is to introduce a suitable approximate control problem that we solve in the finite-dimensional space of…

Numerical Analysis · Mathematics 2023-04-17 Somia Boumimez , Carlos Castro

Aerodynamic shape optimization has many industrial applications. Existing methods, however, are so computationally demanding that typical engineering practices are to either simply try a limited number of hand-designed shapes or restrict…

Computational Engineering, Finance, and Science · Computer Science 2018-02-13 Pierre Baqué , Edoardo Remelli , François Fleuret , Pascal Fua

We discuss methods to construct a polynomial parametrization of some interesting knotted surfaces (knotted spheres, knotted tori and knotted planes) and provide examples.

Geometric Topology · Mathematics 2026-02-17 Louis H. Kauffman , Tumpa Mahato , Rama Mishra

In this paper we consider the approximation of a function by its interpolating multilinear spline and the approximation of its derivatives by the derivatives of the corresponding spline. We derive formulas for the uniform approximation…

Numerical Analysis · Mathematics 2013-08-27 Ryan Anderson , Yuliya Babenko , Tetiana Leskevych

We address the problem of determining correspondences between two images in agreement with a geometric model such as an affine or thin-plate spline transformation, and estimating its parameters. The contributions of this work are…

Computer Vision and Pattern Recognition · Computer Science 2017-04-17 Ignacio Rocco , Relja Arandjelović , Josef Sivic

Chance constrained program where one seeks to minimize an objective over decisions which satisfy randomly disturbed constraints with a given probability is computationally intractable. This paper proposes an approximate approach to address…

Computation · Statistics 2019-12-23 Xun Shen , Jiancang Zhuang , Xingguo Zhang

Understanding the stroke-based evolution of visual artworks is useful for advancing artwork learning, appreciation, and interactive display. While the stroke sequence of renowned artworks remains largely unknown, formulating this sequence…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Jeripothula Prudviraj , Vikram Jamwal

The order in which plane-filling curves visit points in the plane can be exploited to design efficient algorithms. Typically, the curves are useful because they preserve locality: points that are close to each other along the curve tend to…

Computational Geometry · Computer Science 2020-03-31 Herman Haverkort

In this paper we develop proximal methods for statistical learning. Proximal point algorithms are useful in statistics and machine learning for obtaining optimization solutions for composite functions. Our approach exploits closed-form…

Machine Learning · Statistics 2015-06-02 Nicholas G. Polson , James G. Scott , Brandon T. Willard

For a function $f$ that is piecewise analytic on a quasi-smooth arc $\mathcal{L}$ and any $0<\sigma<1$ we construct a sequence of "near-best" polynomials that converge at a rate $e^{-n^{\sigma}}$ at each point of analyticity of $f$ and are…

Complex Variables · Mathematics 2021-02-04 Liudmyla Kryvonos

In Computer Vision, edge detection is one of the favored approaches for feature and object detection in images since it provides information about their objects boundaries. Other region-based approaches use probabilistic analysis such as…

Computer Vision and Pattern Recognition · Computer Science 2019-08-20 Dominique Beaini , Sofiane Achiche , Fabrice Nonez , Maxime Raison

We propose a new algorithm to the problem of polygonal curve approximation based on a multiresolution approach. This algorithm is suboptimal but still maintains some optimality between successive levels of resolution using dynamic…

Computer Vision and Pattern Recognition · Computer Science 2007-05-23 Pierre-François Marteau , Gilbas Ménier

We analyze the space of geometrically continuous piecewise polynomial functions or splines for quadrangular and triangular patches with arbitrary topology and general rational transition maps. To define these spaces of G 1 spline functions,…

Algebraic Geometry · Mathematics 2016-03-24 Bernard Mourrain , Raimundas Vidunas , Nelly Villamizar

The goal of this note is to show that continuous functions may be approximated using scattered translates of the Poisson kernel.

Functional Analysis · Mathematics 2025-09-15 Jeff Ledford

We study continuous approximate solutions to polynomial equations over the ring $C(X)$ of continuous complex-valued functions over a compact Hausdorff space $X$. We show that when $X$ is one-dimensional, the existence of such approximate…

General Topology · Mathematics 2025-10-03 Joshua Lau , Vicente Marin-Marquez

A suitable measure for the similarity of shapes represented by parameterized curves or surfaces is the Fr\'echet distance. Whereas efficient algorithms are known for computing the Fr\'echet distance of polygonal curves, the same problem for…

Computational Geometry · Computer Science 2007-05-23 Helmut Alt , Maike Buchin

Used in the paper is an overcomplete piecewise-polynomial image model incorporating sparsity. The paper shows that using such a model, the edges in the image can be resolved robustly with respect to noise. Two variants of the proposed…

Optimization and Control · Mathematics 2018-10-16 Michaela Novosadová , Pavel Rajmic

By studying $\mathbb{A}^1$-curves on varieties, we propose a geometric approach to strong approximation problem over function fields of complex curves. We prove that strong approximation holds for smooth, low degree affine complete…

Algebraic Geometry · Mathematics 2015-10-16 Qile Chen , Yi Zhu

Kernel approximation using randomized feature maps has recently gained a lot of interest. In this work, we identify that previous approaches for polynomial kernel approximation create maps that are rank deficient, and therefore do not…

Machine Learning · Statistics 2013-12-18 Raffay Hamid , Ying Xiao , Alex Gittens , Dennis DeCoste