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A new method to represent and approximate rotation matrices is introduced. The method represents approximations of a rotation matrix $Q$ with linearithmic complexity, i.e. with $\frac{1}{2}n\lg(n)$ rotations over pairs of coordinates,…

Machine Learning · Computer Science 2014-04-30 Michael Mathieu , Yann LeCun

We show new upper bounds for permanents and hafnians, which are particularly useful for complex matrices. Multidimensional permanents and hyperhafnians are considered as well. The permanental bounds improve on a Hadamard type inequality of…

Classical Analysis and ODEs · Mathematics 2020-05-12 Bero Roos

Motivated by the problems of computing sample covariance matrices, and of transforming a collection of vectors to a basis where they are sparse, we present a simple algorithm that computes an approximation of the product of two n-by-n real…

Data Structures and Algorithms · Computer Science 2015-03-19 Rasmus Pagh

Given a large square matrix $A$ and a sufficiently regular function $f$ so that $f(A)$ is well defined, we are interested in the approximation of the leading singular values and corresponding singular vectors of $f(A)$, and in particular of…

Numerical Analysis · Mathematics 2015-05-14 Sarah W. Gaaf , Valeria Simoncini

We consider the problem of computing the q->p norm of a matrix A, which is defined for p,q \ge 1, as |A|_{q->p} = max_{x !=0 } |Ax|_p / |x|_q. This is in general a non-convex optimization problem, and is a natural generalization of the…

Data Structures and Algorithms · Computer Science 2010-05-04 Aditya Bhaskara , Aravindan Vijayaraghavan

Given a text $T$ of length $n$ and a pattern $P$ of length $m$, the approximate pattern matching problem asks for computation of a particular \emph{distance} function between $P$ and every $m$-substring of $T$. We consider a…

Data Structures and Algorithms · Computer Science 2019-07-24 Jan Studený , Przemysław Uznański

Finding the length of the longest increasing subsequence (LIS) is a classic algorithmic problem. Let $n$ denote the size of the array. Simple $O(n\log n)$ algorithms are known for this problem. We develop a polylogarithmic time randomized…

Data Structures and Algorithms · Computer Science 2013-08-06 M. Saks , C. Seshadhri

Given a univariate polynomial, its abscissa is the maximum real part of its roots. The abscissa arises naturally when controlling linear differential equations. As a function of the polynomial coefficients, the abscissa is H{\"o}lder…

Optimization and Control · Mathematics 2015-07-31 Roxana Heß , Didier Henrion , Jean-Bernard Lasserre , Tien Son Pham

Let $E = L_p, \; 1<p\leq 2,$ and $A : E \to E^*$ be a bounded monotone map such that $0 \in R(A)$. In this paper, we introduce and study an algorithm for approximating zeros of $A$. Furthermore, we study the application of this algorithm to…

Functional Analysis · Mathematics 2022-08-18 Abdulmalik U. Bello , Markjoe O. Uba , Michael T. Omojola , Maria A. Onyido , Cyril I. Udeani

It has been recently shown that $|| F_n(A) ||\leq 2$, where $A$ is a linear continuous operator acting in a Hilbert space, and $F_n$ is the Faber polynomial of degree $n$ corresponding to some convex compact $E\subset \mathbb C$ containing…

Numerical Analysis · Mathematics 2013-10-07 Bernhard Beckermann , Michel Crouzeix

We study the $\ell_1$-low rank approximation problem, where for a given $n \times d$ matrix $A$ and approximation factor $\alpha \geq 1$, the goal is to output a rank-$k$ matrix $\widehat{A}$ for which $$\|A-\widehat{A}\|_1 \leq \alpha…

Data Structures and Algorithms · Computer Science 2020-04-17 Zhao Song , David P. Woodruff , Peilin Zhong

The polynomial-time computability of the permanent over fields of characteristic 3 for k-semi-unitary matrices (i.e. square matrices such that the differences of their Gram matrices and the corresponding identity matrices are of rank k) in…

Computational Complexity · Computer Science 2020-11-04 Anna Knezevic , Greg Cohen , Marina Domanskaya

For logarithmically divergent one-loop lattice Feynman integrals I(p,a), subject to mild general conditions, we prove the following expected and crucial structural result: I(p,a) = f(p)log(aM)+g(p)+h(p,M) up to terms which vanish for…

High Energy Physics - Lattice · Physics 2008-11-26 David H. Adams , Weonjong Lee

We obtain the asymptotic equalities for the least upper bounds of approximations by interpolation trigonometric polynomials with the equidistant nodes $x_k^{(n-1)}=\frac{2k\pi}{2n-1},\ k\in\mathbb{Z},$ in metrics of the spaces $L_p$ on…

Classical Analysis and ODEs · Mathematics 2018-06-08 A. S. Serdyuk , I. V. Sokolenko

We give a polynomial-time constant-factor approximation algorithm for maximum independent set for (axis-aligned) rectangles in the plane. Using a polynomial-time algorithm, the best approximation factor previously known is $O(\log\log n)$.…

Computational Geometry · Computer Science 2021-07-07 Joseph S. B. Mitchell

A fault-tolerant distance labeling scheme assigns a label to each vertex and edge of an undirected weighted graph $G$ with $n$ vertices so that, for any edge set $F$ of size $|F| \leq f$, one can approximate the distance between $p$ and $q$…

Data Structures and Algorithms · Computer Science 2026-04-03 Bernhard Haeupler , Yaowei Long , Antti Roeyskoe , Thatchaphol Saranurak

This work presents a novel matrix-based method for constructing an approximation Hessian using only function evaluations. The method requires less computational power than interpolation-based methods and is easy to implement in matrix-based…

Numerical Analysis · Mathematics 2023-04-07 W. Hare , G. Jarry-Bolduc , C. Planiden

We prove matching direct and inverse theorems for uniform polynomial approximation with $A^*$ weights (a subclass of doubling weights suitable for approximation in the $L_\infty$ norm) having finitely many zeros and not too "rapidly…

Classical Analysis and ODEs · Mathematics 2015-10-27 Kirill A. Kopotun

We propose and investigate two new methods to approximate $f({\bf A}){\bf b}$ for large, sparse, Hermitian matrices ${\bf A}$. The main idea behind both methods is to first estimate the spectral density of ${\bf A}$, and then find…

Numerical Analysis · Computer Science 2018-08-30 Li Fan , David I Shuman , Shashanka Ubaru , Yousef Saad

Given a list of N numbers, the maximum can be computed in N iterations. During these N iterations, the maximum gets updated on average as many times as the Nth harmonic number. We first use this fact to approximate the Nth harmonic number…

Data Structures and Algorithms · Computer Science 2017-04-24 Ali Dasdan
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