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The goal in the min-\# curve simplification problem is to reduce the number of the vertices of a polygonal curve without changing its shape significantly. We study curve-restricted min-\# simplification of polygonal curves, in which the…

Computational Geometry · Computer Science 2019-03-05 Ali Gholami Rudi

We study theoretical and computational aspects of the least squares fit (LSF) of circles and circular arcs. First we discuss the existence and uniqueness of LSF and various parametrization schemes. Then we evaluate several popular circle…

Computer Vision and Pattern Recognition · Computer Science 2007-05-23 N. Chernov , C. Lesort

The least squares method provides the best-fit curve by minimizing the total squares error. In this work, we provide the modified least squares method based on the fractional orthogonal polynomials that belong to the space $M_{n}^{\lambda}…

Numerical Analysis · Mathematics 2024-05-02 Abhishek Kumar Singh , Mani Mehra , Anatoly A. Alikhanov

Tightness is a generalisation of the notion of convexity: a space is tight if and only if it is "as convex as possible", given its topological constraints. For a simplicial complex, deciding tightness has a straightforward exponential time…

Computational Geometry · Computer Science 2018-10-24 Bhaskar Bagchi , Benjamin A. Burton , Basudeb Datta , Nitin Singh , Jonathan Spreer

Plotting solution sets for particular equations may be complicated by the existence of turning points. Here we describe an algorithm which not only overcomes such problematic points, but does so in the most general of settings. Applications…

Numerical Analysis · Mathematics 2011-07-05 Steven Pollack , Daniel Badali , Jonathan Pollack

We develop a new least squares method for solving the second-order elliptic equations in non-divergence form. Two least-squares-type functionals are proposed for solving the equations in two steps. We first obtain a numerical approximation…

Numerical Analysis · Mathematics 2020-04-02 Ruo Li , Fanyi Yang

In the classic circle packing problem, one asks whether a given set of circles can be packed into a given container. Packing problems like this have been shown to be $\mathsf{NP}$-hard. In this paper, we present new sufficient conditions…

Computational Geometry · Computer Science 2018-06-28 Sándor P. Fekete , Sebastian Morr , Christian Scheffer

Many applications of generalised linear models (GLMs) can be improved by applying constraints that impose assumptions on the associations or improve consistency of the estimators. Yet, there are still barriers to the implementation and…

Methodology · Statistics 2026-02-19 Pierre Masselot , Devon Nenon , Jacopo Vanoli , Zaid Chalabi , Antonio Gasparrini

In this paper, we propose a method to obtain a constrained approximation of a rational B\'{e}zier curve by a polynomial B\'{e}zier curve. This problem is reformulated as an approximation problem between two polynomial B\'{e}zier curves…

Numerical Analysis · Mathematics 2014-09-16 Mao Shi , Jiansong Deng

The arithmetic of elliptic curves, namely polynomial addition and scalar multiplication, can be described in terms of global sections of line bundles on $E\times E$ and $E$, respectively, with respect to a given projective embedding of $E$…

Number Theory · Mathematics 2016-01-15 David Kohel

Orthogonal polynomials in two variables on cubic curves are considered, including the case of elliptic curves. For an integral with respect to an appropriate weight function defined on a cubic curve, an explicit basis of orthogonal…

Numerical Analysis · Mathematics 2020-11-24 Marco Fasondini , Sheehan Olver , Yuan Xu

Given two simplicial complexes in R^d, and start and end vertices in each complex, we show how to compute curves (in each complex) between these vertices, such that the Fr\'echet distance between these curves is minimized. As a polygonal…

Computational Geometry · Computer Science 2012-02-28 Sariel Har-Peled , Benjamin Raichel

Many combinatorial optimization problems can be formulated as the search for a subgraph that satisfies certain properties and minimizes the total weight. We assume here that the vertices correspond to points in a metric space and can take…

Data Structures and Algorithms · Computer Science 2024-12-25 Marin Bougeret , Jérémy Omer , Michael Poss

In many astronomical problems one often needs to determine the upper and/or lower boundary of a given data set. An automatic and objective approach consists in fitting the data using a generalised least-squares method, where the function to…

Instrumentation and Methods for Astrophysics · Physics 2015-05-13 N. Cardiel

Converting a parametric curve into the implicit form, which is called implicitization, has always been a popular but challenging problem in geometric modeling and related applications. However, the existing methods mostly suffer from the…

Graphics · Computer Science 2023-02-24 Minghao Guo , Yan Gao , Zheng Pan

Least-squares fits are an important tool in many data analysis applications. In this paper, we review theoretical results, which are relevant for their application to data from counting experiments. Using a simple example, we illustrate the…

Data Analysis, Statistics and Probability · Physics 2019-06-07 Hans Dembinski , Michael Schmelling , Roland Waldi

Finding the product of two polynomials is an essential and basic problem in computer algebra. While most previous results have focused on the worst-case complexity, we instead employ the technique of adaptive analysis to give an improvement…

Symbolic Computation · Computer Science 2010-07-20 Daniel S. Roche

Finding diverse solutions in combinatorial problems recently has received considerable attention (Baste et al. 2020; Fomin et al. 2020; Hanaka et al. 2021). In this paper we study the following type of problems: given an integer $k$, the…

Data Structures and Algorithms · Computer Science 2021-12-16 Tesshu Hanaka , Yasuaki Kobayashi , Kazuhiro Kurita , See Woo Lee , Yota Otachi

This technical note extends recent results on the computational complexity of globally minimizing the error of piecewise-affine models to the related problem of minimizing the error of switching linear regression models. In particular, we…

Machine Learning · Statistics 2016-07-05 Fabien Lauer

Ordinary least squares (OLS) is the default method for fitting linear models, but is not applicable for problems with dimensionality larger than the sample size. For these problems, we advocate the use of a generalized version of OLS…

Methodology · Statistics 2016-06-17 Xiangyu Wang , David Dunson , Chenlei Leng