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Let $(x_n)_{n\geq0}$ be a linear recurrence sequence of order $k\geq2$ satisfying $$x_n=a_1x_{n-1}+a_2x_{n-2}+\dots+a_kx_{n-k}$$ for all integers $n\geq k$, where $a_1,\dots,a_k,x_0,\dots, x_{k-1}\in \mathbb{Z},$ with $a_k\neq0$. In 2017,…

Number Theory · Mathematics 2024-08-14 Deepa Antony , Rupam Barman

Given a linear system, we consider the problem of finding a small set of variables to affect with an input so that the resulting system is controllable. We show that this problem is NP-hard; indeed, we show that even approximating the…

Optimization and Control · Mathematics 2014-05-06 Alex Olshevsky

The complexity class NP of decision problems that can be solved nondeterministically in polynomial time is of great theoretical and practical importance where the notion of polynomial-time reductions between NP-problems is a key concept for…

Computational Complexity · Computer Science 2022-12-23 Hans-Jörg Kreowski , Sabine Kuske , Aaron Lye , Aljoscha Windhorst

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

The computation of the sparse principal component of a matrix is equivalent to the identification of its principal submatrix with the largest maximum eigenvalue. Finding this optimal submatrix is what renders the problem…

Information Theory · Computer Science 2013-12-23 Megasthenis Asteris , Dimitris S. Papailiopoulos , George N. Karystinos

We give an anecdotal discussion of the problem of searching for polynomials with all roots on the unit circle, whose coefficients are rational numbers subject to certain congruence conditions. We illustrate with an example from a…

Number Theory · Mathematics 2007-09-26 Kiran S. Kedlaya

We present the asymptotically fastest known algorithms for some basic problems on univariate polynomial matrices: rank, nullspace, determinant, generic inverse, reduced form. We show that they essentially can be reduced to two computer…

Symbolic Computation · Computer Science 2007-05-23 Claude-Pierre Jeannerod , Gilles Villard

We propose a new algorithm to solve sparse linear systems of equations over the integers. This algorithm is based on a $p$-adic lifting technique combined with the use of block matrices with structured blocks. It achieves a sub-cubic…

Symbolic Computation · Computer Science 2007-05-23 Wayne Eberly , Mark Giesbrecht , Pascal Giorgi , Arne Storjohann , Gilles Villard

We investigate the class of regular-ordered word equations. In such equations, each variable occurs at most once in each side and the order of the variables occurring in both sides is the preserved (the variables can be, however, separated…

Formal Languages and Automata Theory · Computer Science 2017-03-01 Joel D. Day , Florin Manea , Dirk Nowotka

We exhibit a probabilistic algorithm which solves a polynomial system over the rationals defined by a reduced regular sequence. Its bit complexity is roughly quadratic in the B\'ezout number of the system and linear in its bit size. Our…

Algebraic Geometry · Mathematics 2016-12-23 Nardo Gimenez , Guillermo Matera

The works presented in this habilitation concern the algorithmics of polynomials. This is a central topic in computer algebra, with numerous applications both within and outside the field - cryptography, error-correcting codes, etc. For…

Symbolic Computation · Computer Science 2026-03-09 Bruno Grenet

This paper is concerned with exact real solving of well-constrained, bivariate polynomial systems. The main problem is to isolate all common real roots in rational rectangles, and to determine their intersection multiplicities. We present…

Symbolic Computation · Computer Science 2012-03-06 Dimitrios I. Diochnos , Ioannis Z. Emiris , Elias P. Tsigaridas

Many real-world machine learning problems involve inherently hierarchical data, yet traditional approaches rely on Euclidean metrics that fail to capture the discrete, branching nature of hierarchical relationships. We present a theoretical…

Machine Learning · Computer Science 2025-10-02 Gregory D. Baker , Scott McCallum , Dirk Pattinson

A method is described which allows to evaluate efficiently a polynomial in a (possibly trivial) extension of the finite field of its coefficients. Its complexity is shown to be lower than that of standard techniques when the degree of the…

Information Theory · Computer Science 2011-02-24 Davide Schipani , Michele Elia , Joachim Rosenthal

The problem of approximating a dense matrix by a product of sparse factors is a fundamental problem for many signal processing and machine learning tasks. It can be decomposed into two subproblems: finding the position of the non-zero…

Computational Complexity · Computer Science 2022-11-23 Quoc-Tung Le , Elisa Riccietti , Rémi Gribonval

Motivated by a connection with the factorization of multivariate polynomials, we study integral convex polytopes and their integral decompositions in the sense of the Minkowski sum. We first show that deciding decomposability of integral…

Combinatorics · Mathematics 2007-05-23 S. Gao , A. G. B. Lauder

We devise a simple but remarkably accurate iterative routine for calculating the roots of a polynomial of any degree. We demonstrate that our results have significant improvement in accuracy over those obtained by methods used in popular…

Numerical Analysis · Mathematics 2020-09-15 Hashim A. Yamani , Abdulaziz D. Alhaidari

We illustrate an efficient new method for handling polynomial systems with degenerate solution sets. In particular, a corollary of our techniques is a new algorithm to find an isolated point in every excess component of the zero set (over…

Algebraic Geometry · Mathematics 2009-09-25 J. Maurice Rojas

We recently introduced the Fast Newton Transform (FNT), an hierarchical algorithm for performing multivariate Newton interpolation in arbitrary downward closed polynomial spaces of spatial dimension $m$. Here, we analyze the FNT in the…

Numerical Analysis · Mathematics 2025-08-06 Phil-Alexander Hofmann , Damar Wicaksono , Michael Hecht

Causal Bayesian networks are widely used tools for summarising the dependencies between variables and elucidating their putative causal relationships. By restricting the search to trees, for example, learning the optimum from data is…

Computation · Statistics 2025-03-10 Felix L. Rios , Giusi Moffa , Jack Kuipers