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We describe an approximate rational arithmetic with round-off errors (both absolute and relative) controlled by the user. The rounding procedure is based on the continued fraction expansion of real numbers. Results of computer experiments…

Numerical Analysis · Mathematics 2025-10-20 Grigori Litvinov , Anatoli Rodionov , Andrei Chourkin

Using the standard finite element method (FEM) to solve general partial differential equations, the round-off error is found to be proportional to $N^{\beta_{\rm R}}$, with $N$ the number of degrees of freedom (DoFs) and $\beta_{\rm R}$ a…

Numerical Analysis · Mathematics 2022-02-08 Jie Liu , Henk M. Schuttelaars , Matthias Möller

It is well known that the computation of accurate trajectories of the Lorenz system is a difficult problem. Computed solutions are very sensitive to the discretization error determined by the time step size and polynomial order of the…

Numerical Analysis · Mathematics 2013-06-13 Benjamin Kehlet , Anders Logg

The state of the art in approximation algorithms for facility location problems are complicated combinations of various techniques. In particular, the currently best 1.488-approximation algorithm for the uncapacitated facility location…

Data Structures and Algorithms · Computer Science 2016-11-25 Jaroslaw Byrka , Shanfei Li , Bartosz Rybicki

Recently, with the progress of science and the characteristic properties that distinguish the Slepian system called Prolate spheroidal wave functions from the others orthonormal systems, it became clear its important contributions in…

Functional Analysis · Mathematics 2022-06-10 Boulsane Mourad

A consequent approach is proposed to construct symplectic force-gradient algorithms of arbitrarily high orders in the time step for precise integration of motion in classical and quantum mechanics simulations. Within this approach the basic…

Statistical Mechanics · Physics 2009-11-07 Igor Omelyan , Ihor Mryglod , Reinhard Folk

Many popular learning algorithms (E.g. Regression, Fourier-Transform based algorithms, Kernel SVM and Kernel ridge regression) operate by reducing the problem to a convex optimization problem over a vector space of functions. These methods…

Machine Learning · Computer Science 2014-05-13 Amit Daniely , Nati Linial , Shai Shalev-Shwartz

Let $f$ be a fixed (holomorphic or Maass) modular cusp form. Let $\cq$ be a Dirichlet character mod $q$. We describe a fast algorithm that computes the value $L(1/2,f\times\chi_q)$ up to any specified precision. In the case when $q$ is…

Number Theory · Mathematics 2012-02-29 Pankaj Vishe

The high-frequency Helmholtz equation on the entire space is truncated into a bounded domain using the perfectly matched layer (PML) technique and subsequently, discretized by the higher-order finite element method (FEM) and the continuous…

Numerical Analysis · Mathematics 2023-12-06 Yonglin Li , Haijun Wu

We consider the problem of approximating a truncated Gaussian kernel using Fourier (trigonometric) functions. The computation-intensive bilateral filter can be expressed using fast convolutions by applying such an approximation to its range…

Image and Video Processing · Electrical Eng. & Systems 2018-11-07 Sanjay Ghosh , Pravin Nair , Kunal N. Chaudhury

When implementing regular enough functions (e.g., elementary or special functions) on a computing system, we frequently use polynomial approximations. In most cases, the polynomial that best approximates (for a given distance and in a given…

Mathematical Software · Computer Science 2007-05-23 Nicolas Brisebarre , Jean-Michel Muller

This paper presents a novel method of approximating the scalar Wiener-Hopf equation; and therefore constructing an approximate solution. The advantages of this method over the existing methods are reliability and explicit error bounds.…

Complex Variables · Mathematics 2015-06-15 Anastasia V. Kisil

We provide a simple and novel algorithmic design technique, for which we call iterative partial rounding, that gives a tight rounding-based approximation for vertex cover with hard capacities (VC-HC). In particular, we obtain an…

Data Structures and Algorithms · Computer Science 2016-10-17 Mong-Jen Kao

Compared to other symplectic integrators (the Wisdom and Holman map and its higher order generalizations) that also take advantage of the hierarchical nature of the motion of the planets around the central star, our methods require solving…

Computational Physics · Physics 2022-06-15 M. Antoñana , E. Alberdi , J. Makazaga , A. Murua

We study the complexity of the classic capacitated k-median and k-means problems parameterized by the number of centers, k. These problems are notoriously difficult since the best known approximation bound for high dimensional Euclidean…

Data Structures and Algorithms · Computer Science 2022-08-31 Vincent Cohen-Addad , Jason Li

Hurwitz (1887) defined a continued fraction algorithm for complex numbers which is better behaved in many respects than a more "natural" extension of the classical continued fraction algorithm to the complex plane would be. Although the…

Number Theory · Mathematics 2018-01-23 David Simmons

Methods of finding good quantum error correcting codes are discussed, and many example codes are presented. The recipe C_2^{\perp} \subseteq C_1, where C_1 and C_2 are classical codes, is used to obtain codes for up to 16 information qubits…

Quantum Physics · Physics 2008-12-18 Andrew Steane

We show that real-value approximations of Kolmogorov-Chaitin (K_m) using the algorithmic Coding theorem as calculated from the output frequency of a large set of small deterministic Turing machines with up to 5 states (and 2 symbols), is in…

Information Theory · Computer Science 2013-12-12 Fernando Soler-Toscano , Hector Zenil , Jean-Paul Delahaye , Nicolas Gauvrit

Random Fourier Features (RFF) is among the most popular and broadly applicable approaches for scaling up kernel methods. In essence, RFF allows the user to avoid costly computations on a large kernel matrix via a fast randomized…

Machine Learning · Statistics 2023-02-23 Junwen Yao , N. Benjamin Erichson , Miles E. Lopes

Inferential models (IMs) offer provably reliable, data-driven, possibilistic statistical inference. But despite the IM framework's theoretical and foundational advantages, efficient computation is a challenge. This paper presents a simple…

Computation · Statistics 2025-07-09 Leonardo Cella , Ryan Martin