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Related papers: Zolotarev Iterations for the Matrix Square Root

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It is well known that a family of $n\times n$ commuting matrices can be simultaneously triangularized by a unitary similarity transformation. The diagonal entries of the triangular matrices define the $n$ joint eigenvalues of the family. In…

Numerical Analysis · Mathematics 2024-11-05 Haoze He , Daniel Kressner , Bor Plestenjak

We present a new algorithm for reconstructing an exact algebraic number from its approximate value using an improved parameterized integer relation construction method. Our result is consistent with the existence of error controlling on…

Computational Complexity · Computer Science 2009-02-06 Xiaolin Qin , Yong Feng , Jingwei Chen , Jingzhong Zhang

We study randomized sketching methods for approximately solving least-squares problem with a general convex constraint. The quality of a least-squares approximation can be assessed in different ways: either in terms of the value of the…

Optimization and Control · Mathematics 2014-11-04 Mert Pilanci , Martin J. Wainwright

Given a map f:Z-->Z and an initial argument alpha, we can iterate the map to get a finite set of iterates modulo a prime p. In particular, for a quadratic map f(z)=z^2 +c, c constant, work by Pollard suggests that this set should have…

Number Theory · Mathematics 2012-01-26 William Worden

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

We investigate the problem of approximating the matrix function $f(A)$ by $r(A)$, with $f$ a Markov function, $r$ a rational interpolant of $f$, and $A$ a symmetric Toeplitz matrix. In a first step, we obtain a new upper bound for the…

Numerical Analysis · Mathematics 2022-01-19 Bernhard Beckermann , Joanna Bisch , Robert Luce

We introduce a new iterative root-finding method for complex polynomials, dubbed {\it Newton-Ellipsoid} method. It is inspired by the Ellipsoid method, a classical method in optimization, and a property of Newton's Method derived in…

Numerical Analysis · Computer Science 2014-10-09 Bahman Kalantari , Eric Lee

We study implicit regularization when optimizing an underdetermined quadratic objective over a matrix $X$ with gradient descent on a factorization of $X$. We conjecture and provide empirical and theoretical evidence that with small enough…

Machine Learning · Statistics 2017-05-26 Suriya Gunasekar , Blake Woodworth , Srinadh Bhojanapalli , Behnam Neyshabur , Nathan Srebro

We present a novel iterative algorithm for approximating the linear least squares solution with low complexity. After a motivation of the algorithm we discuss the algorithm's properties including its complexity, and we present theoretical…

Data Structures and Algorithms · Computer Science 2016-11-15 Michael Lunglmayr , Christoph Unterrieder , Mario Huemer

Bernstein-Sato polynomial of a hypersurface is an important object with numerous applications. It is known, that it is complicated to obtain it computationally, as a number of open questions and challenges indicate. In this paper we propose…

Algebraic Geometry · Mathematics 2010-03-22 Viktor Levandovskyy , Jorge Martín-Morales

We show how rational function approximations to the logarithm, such as $\log z \approx (z^2 - 1)/(z^2 + 6z + 1)$, can be turned into fast algorithms for approximating the determinant of a very large matrix. We empirically demonstrate that…

Data Structures and Algorithms · Computer Science 2024-05-07 Thomas Colthurst , Srinivas Vasudevan , James Lottes , Brian Patton

Square matrices appear in many machine learning problems and models. Optimization over a large square matrix is expensive in memory and in time. Therefore an economic approximation is needed. Conventional approximation approaches factorize…

Machine Learning · Computer Science 2021-09-20 Ruslan Khalitov , Tong Yu , Lei Cheng , Zhirong Yang

We propose an iterative algorithm for low-rank matrix completion that can be interpreted as an iteratively reweighted least squares (IRLS) algorithm, a saddle-escaping smoothing Newton method or a variable metric proximal gradient method…

Optimization and Control · Mathematics 2021-06-07 Christian Kümmerle , Claudio Mayrink Verdun

We present the submatrix method, a highly parallelizable method for the approximate calculation of inverse p-th roots of large sparse symmetric matrices which are required in different scientific applications. We follow the idea of…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-06 Michael Lass , Stephan Mohr , Hendrik Wiebeler , Thomas D. Kühne , Christian Plessl

A proof for a conjecture by Shadrin and Zvonkine, relating the entries of a matrix arising in the study of Hurwitz numbers to a certain sequence of rational numbers, is given. The main tools used are iteration matrices of formal power…

Combinatorics · Mathematics 2011-11-10 Matthias Aschenbrenner

In these notes, we consider the problem of finding the logarithm or the square root of a real matrix. It is known that for every real n x n matrix, A, if no real eigenvalue of A is negative or zero, then A has a real logarithm, that is,…

General Mathematics · Mathematics 2013-11-12 Jean Gallier

Hierarchical matrices approximate a given matrix by a decomposition into low-rank submatrices that can be handled efficiently in factorized form. $\mathcal{H}^2$-matrices refine this representation following the ideas of fast multipole…

Numerical Analysis · Mathematics 2024-04-24 Steffen Börm

In an influential 1877 paper, Zolotarev asked and answered four questions about polynomial and rational approximation. We ask and answer two questions: what are the best rational approximants $r$ and $s$ to $\sqrt{z}$ and $\mbox{sign}(z)$…

Classical Analysis and ODEs · Mathematics 2020-11-24 Evan S. Gawlik , Yuji Nakatsukasa

In the past few years, successive improvements of the asymptotic complexity of square matrix multiplication have been obtained by developing novel methods to analyze the powers of the Coppersmith-Winograd tensor, a basic construction…

Data Structures and Algorithms · Computer Science 2021-10-05 François Le Gall , Florent Urrutia

The square root of Not is a logical operator of importance in quantum computing theory and of interest as a mathematical object in its own right. In physics, it is a square complex matrix of dimension 2. In the present work it is a complex…

Other Computer Science · Computer Science 2024-06-11 Eduardo Mizraji
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