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Matrix factorization methods are important tools in data mining and analysis. They can be used for many tasks, ranging from dimensionality reduction to visualization. In this paper we concentrate on the use of matrix factorizations for…

Machine Learning · Computer Science 2017-07-28 Sanjar Karaev , Pauli Miettinen

In this paper, we consider the existence of a factorization of a monic, bounded motion polynomial. We prove existence of factorizations, possibly after multiplication with a real polynomial and provide algorithms for computing polynomial…

Symbolic Computation · Computer Science 2015-02-27 Zijia Li , Josef Schicho , Hans-Peter Schröcker

We determine the power of the weighted sum scalarization with respect to the computation of approximations for general multiobjective minimization and maximization problems. Additionally, we introduce a new multi-factor notion of…

Data Structures and Algorithms · Computer Science 2021-12-15 Cristina Bazgan , Stefan Ruzika , Clemens Thielen , Daniel Vanderpooten

Polynomial factorization and root finding are among the most standard themes of computational mathematics. Yet still, little has been done for polynomials over quaternion algebras, with the single exception of Hamiltonian quaternions for…

Symbolic Computation · Computer Science 2023-05-04 Przemysław Koprowski

Boolean matrix factorization (BMF) approximates a given binary input matrix as the product of two smaller binary factors. Unlike binary matrix factorization based on standard arithmetic, BMF employs the Boolean OR and AND operations for the…

Information Retrieval · Computer Science 2025-12-05 Christos Kolomvakis , Thomas Bobille , Arnaud Vandaele , Nicolas Gillis

In light of recent data science trends, new interest has fallen in alternative matrix factorizations. By this, we mean various ways of factorizing particular data matrices so that the factors have special properties and reveal insights into…

Optimization and Control · Mathematics 2023-02-21 Andries Steenkamp

In this paper, we intend to present a new algorithm to factorize large numbers. According to the algorithm proposed here, we prove that there is a common factor between p and q. With this procedure, the time of factorization considerably…

Quantum Physics · Physics 2007-05-23 Fabiano Sutter de Oliveira

In this paper, we propose a new and simple approach to the approximation algorithms that are modified and improved from our published results. The computational and graphical examples are presented with the aid of Maple procedures.

Numerical Analysis · Mathematics 2025-06-24 Quan Le Phuong

By establishing an interesting connection between ordinary Bell polynomials and rational convolution powers, some composition and inverse relations of Bell polynomials as well as explicit expressions for convolution roots of sequences are…

Classical Analysis and ODEs · Mathematics 2023-11-16 Hamed Taghavian

The Boolean matrix factorization problem consists in approximating a matrix by the Boolean product of two smaller Boolean matrices. To obtain optimal solutions when the matrices to be factorized are small, we propose SAT and MaxSAT…

Machine Learning · Computer Science 2021-06-21 Florent Avellaneda , Roger Villemaire

A new efficient algorithm is proposed for factoring polynomials over an algebraic extension field. The extension field is defined by a polynomial ring modulo a maximal ideal. If the maximal ideal is given by its Groebner basis, no extra…

Symbolic Computation · Computer Science 2010-10-04 Yao Sun , Dingkang Wang

Multipoint polynomial evaluation and interpolation are fundamental for modern symbolic and numerical computing. The known algorithms solve both problems over any field of constants in nearly linear arithmetic time, but the cost grows to…

Numerical Analysis · Mathematics 2017-04-19 Victor Y. Pan

The performance of numerical micromagnetic models is limited by the demagnetizing field computation, which typically accounts for the majority of the computation time. For magnetization dynamics simulations explicit evaluation methods are…

Computational Physics · Physics 2022-06-15 Serban Lepadatu

The most popular method for computing the matrix logarithm is a combination of the inverse scaling and squaring method in conjunction with a Pad\'e approximation, sometimes accompanied by the Schur decomposition. The main computational…

Numerical Analysis · Mathematics 2024-01-19 Elias Jarlebring , Jorge Sastre , J. Javier Ibáñez González

We present an algorithm to compute all factorizations into linear factors of univariate polynomials over the split quaternions, provided such a factorization exists. Failure of the algorithm is equivalent to non-factorizability for which we…

Rings and Algebras · Mathematics 2022-11-08 Daniel F. Scharler , Hans-Peter Schröcker

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

Matrix functions are a central topic of linear algebra, and problems requiring their numerical approximation appear increasingly often in scientific computing. We review various limited-memory methods for the approximation of the action of…

Numerical Analysis · Mathematics 2020-10-26 Stefan Güttel , Daniel Kressner , Kathryn Lund

This paper is concerned with factor left prime factorization problems for multivariate polynomial matrices without full row rank. We propose a necessary and sufficient condition for the existence of factor left prime factorizations of a…

Symbolic Computation · Computer Science 2020-10-15 Dong Lu , Dingkang Wang , Fanghui Xiao

In this paper, a randomized algorithm for deciding the irreducibility of an irreducible polynomial and factoring a reducible polynomial over the field of rational numbers is presented. The main idea underlying the algorithm is based on…

General Mathematics · Mathematics 2019-12-30 Duggirala Meher Krishna , Duggirala Ravi

Weighted least squares polynomial approximation uses random samples to determine projections of functions onto spaces of polynomials. It has been shown that, using an optimal distribution of sample locations, the number of samples required…

Numerical Analysis · Mathematics 2017-10-10 Abdul-Lateef Haji-Ali , Fabio Nobile , Raúl Tempone , Sören Wolfers