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This paper studies the commonly utilized windowed Anderson acceleration (AA) algorithm for fixed-point methods, $x^{(k+1)}=q(x^{(k)})$. It provides the first proof that when the operator $q$ is linear and symmetric the windowed AA, which…

Numerical Analysis · Mathematics 2025-08-01 Casey Garner , Gilad Lerman , Teng Zhang

We present new algorithms for $M$-estimators of multivariate scatter and location and for symmetrized $M$-estimators of multivariate scatter. The new algorithms are considerably faster than currently used fixed-point and related algorithms.…

Computation · Statistics 2015-12-10 Lutz Duembgen , Klaus Nordhausen , Heike Schuhmacher

Approximate computing has shown to provide new ways to improve performance and power consumption of error-resilient applications. While many of these applications can be found in image processing, data classification or machine learning, we…

Numerical Analysis · Computer Science 2017-03-08 Michael Lass , Thomas D. Kühne , Christian Plessl

Acceleration of algorithms is becoming a crucial problem, if larger data sets are to be processed. Evaluation of algorithms is mostly done by using computational geometry approach and evaluation of computational complexity. However in…

Computational Geometry · Computer Science 2022-08-29 Vaclav Skala

An efficient hybrid numerical method for multiple scattering calculations is proposed. We use the well established doubling--adding method to find the reflection function of the lowermost homogeneous slab comprising the atmosphere of our…

Instrumentation and Methods for Astrophysics · Physics 2016-11-04 Kiyoshi Kawabata

Boson Sampling is a computational task strongly believed to be hard for classical computers, but efficiently solvable by orchestrated bosonic interference in a specialised quantum computer. Current experimental schemes, however, are still…

This paper presents in detail the originally developed Quadratic Point Estimate Method (QPEM), aimed at efficiently and accurately computing the first four output moments of probabilistic distributions, using 2n^2+1 sample (or sigma)…

Numerical Analysis · Mathematics 2024-03-21 Minhyeok Ko , Konstantinos G. Papakonstantinou

In this paper, we propose and analyze a fast two-point gradient algorithm for solving nonlinear ill-posed problems, which is based on the sequential subspace optimization method. A complete convergence analysis is provided under the…

Analysis of PDEs · Mathematics 2019-11-06 Guangyu Gao , Bo Han , Shanshan Tong

We describe a subdivision algorithm for isolating the complex roots of a polynomial $F\in\mathbb{C}[x]$. Given an oracle that provides approximations of each of the coefficients of $F$ to any absolute error bound and given an arbitrary…

Numerical Analysis · Computer Science 2016-11-09 Ruben Becker , Michael Sagraloff , Vikram Sharma , Chee Yap

A fast and accurate algorithm for the computation of Gauss-Hermite and generalized Gauss-Hermite quadrature nodes and weights is presented. The algorithm is based on Newton's method with carefully selected initial guesses for the nodes and…

Numerical Analysis · Mathematics 2014-10-21 Alex Townsend , Thomas Trogdon , Sheehan Olver

We present experimental and theoretical results on a method that applies a numerical solver iteratively to solve several non-negative quadratic programming problems in geometric optimization. The method gains efficiency by exploiting the…

Computational Geometry · Computer Science 2023-11-21 Siu-Wing Cheng , Man Ting Wong

We consider methods for finding high-precision approximations to simple zeros of smooth functions. As an application, we give fast methods for evaluating the elementary functions log(x), exp(x), sin(x) etc. to high precision. For example,…

Numerical Analysis · Computer Science 2010-06-01 Richard P. Brent

A new algorithm for computing the multivariate Fa\`a di Bruno's formula is provided. We use a symbolic approach based on the classical umbral calculus that turns the computation of the multivariate Fa\`a di Bruno's formula into a suitable…

Combinatorics · Mathematics 2010-12-30 E. Di Nardo , G. Guarino , D. Senato

The usual formulation of efficient division uses Newton iteration to compute an inverse in a related domain where multiplicative inverses exist. On one hand, Newton iteration allows quotients to be calculated using an efficient…

Symbolic Computation · Computer Science 2023-06-29 Stephen M. Watt

We have designed a new symbolic-numeric strategy to compute efficiently and accurately floating point Puiseux series defined by a bivariate polynomial over an algebraic number field. In essence, computations modulo a well chosen prime $p$…

Symbolic Computation · Computer Science 2008-03-21 Adrien Poteaux , Marc Rybowicz

We consider the problem of numerically computing a critical point of a functional $J\colon M\rightarrow R$ where $M$ is a Riemannian manifold. Due to local quadratic convergence a popular choice to solve this problem is the geometric Newton…

General Mathematics · Mathematics 2016-07-14 Markus Sprecher

There are thousands of papers on rootfinding for nonlinear scalar equations. Here is one more, to talk about an apparently new method, which I call ``Inverse Cubic Iteration'' (ICI) in analogy to the Inverse Quadratic Iteration in Richard…

Numerical Analysis · Mathematics 2020-07-15 Robert M. Corless

A general quantum algorithm for solving a problem is discussed. The number of steps required to solve a problem using this method is independent of the number of cases that has to be considered classically. Hence, it is more efficient than…

Quantum Physics · Physics 2007-05-23 M. P John

In the computation of Feynman integrals which evaluate to multiple polylogarithms one encounters quite often square roots. To express the Feynman integral in terms of multiple polylogarithms, one seeks a transformation of variables, which…

High Energy Physics - Theory · Physics 2018-12-07 Marco Besier , Duco van Straten , Stefan Weinzierl

We present squareplus, an activation function that resembles softplus, but which can be computed using only algebraic operations: addition, multiplication, and square-root. Because squareplus is ~6x faster to evaluate than softplus on a CPU…

Machine Learning · Computer Science 2021-12-23 Jonathan T. Barron