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We study algorithms for the fast computation of modular inverses. Newton-Raphson iteration over $p$-adic numbers gives a recurrence relation computing modular inverse modulo $p^m$, that is logarithmic in $m$. We solve the recurrence to…

Symbolic Computation · Computer Science 2019-04-22 Jean-Guillaume Dumas

We consider high-order splitting schemes for large-scale differential Riccati equations. Such equations arise in many different areas and are especially important within the field of optimal control. In the large-scale case, it is critical…

Optimization and Control · Mathematics 2018-08-14 Tony Stillfjord

We introduce a new numerical method, based on Bernoulli polynomials, for solving multiterm variable-order fractional differential equations. The variable-order fractional derivative was considered in the Caputo sense, while the…

Numerical Analysis · Mathematics 2021-11-18 Somayeh Nemati , Pedro M. Lima , Delfim F. M. Torres

We propose faster methods for unconstrained optimization of \emph{structured convex quartics}, which are convex functions of the form \begin{equation*} f(x) = c^\top x + x^\top \mathbf{G} x + \mathbf{T}[x,x,x] + \frac{1}{24} \mathopen\|…

Optimization and Control · Mathematics 2018-12-27 Brian Bullins

The application of error-free transformation (EFT) is recently being developed to solve ill-conditioned problems. It can reduce the number of arithmetic operations required, compared with multiple precision arithmetic, and also be applied…

Numerical Analysis · Mathematics 2019-10-24 Tomonori Kouya

The Riemann problem for first-order hyperbolic systems of partial differential equations is of fundamental importance for both theoretical and numerical purposes. Many approximate solvers have been developed for such systems; exact solution…

Numerical Analysis · Mathematics 2024-02-22 Carlos Muñoz Moncayo , Manuel Quezada de Luna , David I. Ketcheson

The paper concerns numerical algorithms for solving the Beltrami equation $f_{\bar{z}}(z)=\mu(z) f_z(z)$ for a compactly supported $\mu$. First, we study an efficient algorithm that has been proposed in the literature, and present its…

Numerical Analysis · Mathematics 2007-05-23 Denis Gaydashev , Dmitry Khmelev

The Fast Fourier Transform (FFT) over a finite field $\mathbb{F}_q$ computes evaluations of a given polynomial of degree less than $n$ at a specifically chosen set of $n$ distinct evaluation points in $\mathbb{F}_q$. If $q$ or $q-1$ is a…

Computational Complexity · Computer Science 2023-10-24 Songsong Li , Chaoping Xing

Fast linear transforms are ubiquitous in machine learning, including the discrete Fourier transform, discrete cosine transform, and other structured transformations such as convolutions. All of these transforms can be represented by dense…

Machine Learning · Computer Science 2021-01-01 Tri Dao , Albert Gu , Matthew Eichhorn , Atri Rudra , Christopher Ré

An efficient procedure for error-value calculations based on fast discrete Fourier transforms (DFT) in conjunction with Berlekamp-Massey-Sakata algorithm for a class of affine variety codes is proposed. Our procedure is achieved by…

Information Theory · Computer Science 2012-10-02 Hajime Matsui

In this paper, we present novel deterministic algorithms for multiplying two $n \times n$ matrices approximately. Given two matrices $A,B$ we return a matrix $C'$ which is an \emph{approximation} to $C = AB$. We consider the notion of…

Data Structures and Algorithms · Computer Science 2014-08-21 Shiva Manne , Manjish Pal

This work develops novel rational Krylov methods for updating a large-scale matrix function f(A) when A is subject to low-rank modifications. It extends our previous work in this context on polynomial Krylov methods, for which we present a…

Numerical Analysis · Mathematics 2020-08-27 Bernhard Beckermann , Alice Cortinovis , Daniel Kressner , Marcel Schweitzer

This paper is concerned with the efficient evaluation of higher-order derivatives of functions $f$ that are composed of matrix operations. I.e., we want to compute the $D$-th derivative tensor $\nabla^D f(X) \in \mathbb R^{N^D}$, where…

Data Structures and Algorithms · Computer Science 2016-09-08 Sebastian F. Walter

Motivated by recent Linear Programming solvers, we design dynamic data structures for maintaining the inverse of an $n\times n$ real matrix under $\textit{low-rank}$ updates, with polynomially faster amortized running time. Our data…

Data Structures and Algorithms · Computer Science 2020-04-17 Shunhua Jiang , Zhao Song , Omri Weinstein , Hengjie Zhang

In this work, we propose an observation system based on the available data which solution is one-be-one mapping to the forward problem(with the unknown initial function) solution. It implies their solutions share the same linear structure…

Numerical Analysis · Mathematics 2026-04-27 Dakang Cen , Zhiyuan Li , Wenlong Zhang

In this paper, we explore quadratures for the evaluation of $B^T \phi(A) B$ where $A$ is a symmetric positive-definite (s.p.d.) matrix in $\mathbb{R}^{n \times n}$, $B$ is a tall matrix in $\mathbb{R}^{n \times p}$, and $\phi(\cdot)$…

Numerical Analysis · Mathematics 2025-01-13 Jörn Zimmerling , Vladimir Druskin , Valeria Simoncini

Several linear algebra routines for quantum computing use a basis of tensor products of identity and Pauli operators to describe linear operators, and obtaining the coordinates for any given linear operator from its matrix representation…

Quantum Physics · Physics 2020-11-19 Daniel Gunlycke , Mark C. Palenik , Alex R. Emmert , Sean A. Fischer

We address optimization of nonlinear functions of the form $f(Wx)$, where $f:\R^d\to \R$ is a nonlinear function, $W$ is a $d\times n$ matrix, and feasible $x$ are in some large finite set $F$ of integer points in $\R^n$. One motivation is…

Combinatorics · Mathematics 2008-07-25 Yael Berstein , Jon Lee , Shmuel Onn , Robert Weismantel

We consider the problem of efficiently solving large-scale linear least squares problems that have one or more linear constraints that must be satisfied exactly. Whilst some classical approaches are theoretically well founded, they can face…

Numerical Analysis · Mathematics 2021-12-24 Jennifer Scott , Miroslav Tuma

The Schur decomposition of a square matrix $A$ is an important intermediate step of state-of-the-art numerical algorithms for addressing eigenvalue problems, matrix functions, and matrix equations. This work is concerned with the following…

Numerical Analysis · Mathematics 2022-03-22 Zvonimir Bujanović , Daniel Kressner , Christian Schröder
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