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We give an algorithm for computing all roots of polynomials over a univariate power series ring over an exact field $\mathbb{K}$. More precisely, given a precision $d$, and a polynomial $Q$ whose coefficients are power series in $x$, the…

Symbolic Computation · Computer Science 2017-05-31 Vincent Neiger , Johan Rosenkilde , Eric Schost

We propose new algorithms for computing triangular decompositions of polynomial systems incrementally. With respect to previous works, our improvements are based on a {\em weakened} notion of a polynomial GCD modulo a regular chain, which…

Symbolic Computation · Computer Science 2011-04-06 Changbo Chen , Marc Moreno Maza

We present a fast Jacobi-like algorithm for computing the eigenvalues, and optionally the eigenvectors, of a real normal matrix. The method gains a computational advantage by using Paardekooper's method for skew-symmetric matrices The…

Numerical Analysis · Mathematics 2026-05-27 Simon Mataigne , P. -A. Absil

We consider the problem of finding a sparse multiple of a polynomial. Given f in F[x] of degree d over a field F, and a desired sparsity t, our goal is to determine if there exists a multiple h in F[x] of f such that h has at most t…

Symbolic Computation · Computer Science 2011-01-04 Mark Giesbrecht , Daniel S. Roche , Hrushikesh Tilak

We take an existing implementation of an algorithm for the maximum clique problem and modify it so that we can distribute it over an ad-hoc cluster of machines. Our goal was to achieve a significant speedup in performance with minimal…

Data Structures and Algorithms · Computer Science 2013-03-22 Ciaran McCreesh , Patrick Prosser

Recently, the butterfly approximation scheme and hierarchical approximations have been proposed for the efficient computation of integral transforms with oscillatory and with asymptotically smooth kernels. Combining both approaches, we…

Numerical Analysis · Mathematics 2016-06-13 Stefan Kunis , Ines Melzer

Sample- and computationally-efficient distribution estimation is a fundamental tenet in statistics and machine learning. We present SURF, an algorithm for approximating distributions by piecewise polynomials. SURF is: simple, replacing…

Machine Learning · Statistics 2021-02-15 Yi Hao , Ayush Jain , Alon Orlitsky , Vaishakh Ravindrakumar

In this paper, we apply results on number systems based on continued fraction expansions to modular arithmetic. We provide two new algorithms in order to compute modular multiplication and modular division. The presented algorithms are…

Data Structures and Algorithms · Computer Science 2013-03-15 Mourad Gouicem

The theoretical computation of isotopic distribution of compounds is crucial in many important applications of mass spectrometry, especially as machine precision grows. A considerable amount of good tools have been created in the last…

Computational Engineering, Finance, and Science · Computer Science 2020-04-17 Patrick Kreitzberg , Jake Pennington , Kyle Lucke , Oliver Serang

This survey highlights the recent advances in algorithms for numerical linear algebra that have come from the technique of linear sketching, whereby given a matrix, one first compresses it to a much smaller matrix by multiplying it by a…

Data Structures and Algorithms · Computer Science 2015-02-11 David P. Woodruff

Sine-skewed circular distributions are identifiable and have easily-computable trigonometric moments and a simple random number generation algorithm, whereas they are known to have relatively low levels of asymmetry. This study proposes a…

Methodology · Statistics 2024-02-16 Yoichi Miyata , Takayuki Shiohama , Toshihiro Abe

We use matrix iteration theory to characterize acceleration in smooth games. We define the spectral shape of a family of games as the set containing all eigenvalues of the Jacobians of standard gradient dynamics in the family. Shapes…

Machine Learning · Computer Science 2020-03-10 Waïss Azizian , Damien Scieur , Ioannis Mitliagkas , Simon Lacoste-Julien , Gauthier Gidel

We present new, faster pseudopolynomial time algorithms for the $k$-Subset Sum problem, defined as follows: given a set $Z$ of $n$ positive integers and $k$ targets $t_1, \ldots, t_k$, determine whether there exist $k$ disjoint subsets…

Data Structures and Algorithms · Computer Science 2022-01-04 Antonis Antonopoulos , Aris Pagourtzis , Stavros Petsalakis , Manolis Vasilakis

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

Submodular optimization generalizes many classic problems in combinatorial optimization and has recently found a wide range of applications in machine learning (e.g., feature engineering and active learning). For many large-scale…

Data Structures and Algorithms · Computer Science 2023-04-11 Matthew Fahrbach , Vahab Mirrokni , Morteza Zadimoghaddam

We perform forward error analysis for a large class of recursive matrix multiplication algorithms in the spirit of [D. Bini and G. Lotti, Stability of fast algorithms for matrix multiplication, Numer. Math. 36 (1980), 63--72]. As a…

Numerical Analysis · Mathematics 2007-05-23 James Demmel , Ioana Dumitriu , Olga Holtz , Robert Kleinberg

We describe a novel approach to accelerating Monte Carlo Markov Chains. Our focus is cosmological parameter estimation, but the algorithm is applicable to any problem for which the likelihood surface is a smooth function of the free…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-20 Adam Bouland , Richard Easther , Katherine Rosenfeld

In this work, we study how to use sampling to speed up mechanisms for answering adaptive queries into datasets without reducing the accuracy of those mechanisms. This is important to do when both the datasets and the number of queries asked…

Machine Learning · Computer Science 2020-01-03 Benjamin Fish , Lev Reyzin , Benjamin I. P. Rubinstein

A novel parallel algorithm for matrix multiplication is presented. The hyper-systolic algorithm makes use of a one-dimensional processor abstraction. The procedure can be implemented on all types of parallel systems. It can handle…

Mathematical Software · Computer Science 2007-05-23 Thomas Lippert , Nikolay Petkov , Paolo Palazzari , Klaus Schilling

We study the structure of the set of all possible affine hyperplane sections of a convex polytope. We present two different cell decompositions of this set, induced by hyperplane arrangements. Using our decomposition, we bound the number of…

Combinatorics · Mathematics 2025-06-02 Marie-Charlotte Brandenburg , Jesús A. De Loera , Chiara Meroni