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We show that a formalism proposed by Creutz to evaluate Grassmann integrals provides an algorithm of complexity $O(2^n n^3)$ to compute the generating function for the sum of the permanental minors of a matrix of order $n$. This algorithm…

High Energy Physics - Lattice · Physics 2016-02-02 P. Butera , M. Pernici

We give two algorithms for output-sparse matrix multiplication (OSMM), the problem of multiplying two $n \times n$ matrices $A, B$ when their product $AB$ is promised to have at most $O(n^{\delta})$ many non-zero entries for a given value…

Data Structures and Algorithms · Computer Science 2025-08-15 Huck Bennett , Karthik Gajulapalli , Alexander Golovnev , Evelyn Warton

In this paper, we propose two new interpolation algorithms for sparse multivariate polynomials represented by a straight-line program(SLP). Both of our algorithms work over any finite fields $F_q$ with large characteristic. The first one is…

Symbolic Computation · Computer Science 2020-02-11 Qiao-Long Huang

In this work, we present the \emph{twiddless fast Fourier transform (TFFT)}, a novel algorithm for computing the $N$-point discrete Fourier transform (DFT). The TFFT's divide strategy builds on recent results that decimate an $N$-point…

Computational Complexity · Computer Science 2025-12-23 Saulo Queiroz

In 1969, Strassen shocked the world by showing that two n x n matrices could be multiplied in time asymptotically less than $O(n^3)$. While the recursive construction in his algorithm is very clear, the key gain was made by showing that 2 x…

Data Structures and Algorithms · Computer Science 2017-09-01 Joshua A. Grochow , Cristopher Moore

We give a new proof of F\"urer's bound for the cost of multiplying n-bit integers in the bit complexity model. Unlike F\"urer, our method does not require constructing special coefficient rings with "fast" roots of unity. Moreover, we prove…

Computational Complexity · Computer Science 2014-07-15 David Harvey , Joris van der Hoeven , Grégoire Lecerf

We present a novel algorithm for calculating the discrete fractional Hadamard transform for data vectors whose size N is a power of two. A direct method for calculation of the discrete fractional Hadamard transform requires $N^2$…

Data Structures and Algorithms · Computer Science 2015-07-21 Aleksandr Cariow , Dorota Majorkowska-Mech

We consider the problem of interpolating a sparse multivariate polynomial over a finite field, represented with a black box. Building on the algorithm of Ben-Or and Tiwari for interpolating polynomials over rings with characteristic zero,…

Symbolic Computation · Computer Science 2020-02-11 Qiao-Long Huang

We present a non-commutative algorithm for the multiplication of a 2 x 2 block-matrix by its adjoint, defined by a matrix ring anti-homomorphism. This algorithm uses 5 block products (3 recursive calls and 2 general products)over C or in…

Symbolic Computation · Computer Science 2021-01-05 Jean-Guillaume Dumas , Clément Pernet , Alexandre Sedoglavic

We describe a new algorithm for computing exp(f) where f is a power series in C[[x]]. If M(n) denotes the cost of multiplying polynomials of degree n, the new algorithm costs (2.1666... + o(1)) M(n) to compute exp(f) to order n. This…

Symbolic Computation · Computer Science 2009-11-17 David Harvey

For a square-free bivariate polynomial $p$ of degree $n$ we introduce a simple and fast numerical algorithm for the construction of $n\times n$ matrices $A$, $B$, and $C$ such that $\det(A+xB+yC)=p(x,y)$. This is the minimal size needed to…

Numerical Analysis · Mathematics 2020-02-18 Bor Plestenjak

In this work a rationalized algorithm for calculating the quotient of two complex numbers is presented which reduces the number of underlying real multiplications. The performing of a complex number division using the naive method takes 4…

Data Structures and Algorithms · Computer Science 2016-08-31 Aleksandr Cariow

For most deep learning algorithms training is notoriously time consuming. Since most of the computation in training neural networks is typically spent on floating point multiplications, we investigate an approach to training that eliminates…

Machine Learning · Computer Science 2016-02-29 Zhouhan Lin , Matthieu Courbariaux , Roland Memisevic , Yoshua Bengio

In this paper, we study the nonnegative matrix factorization problem under the separability assumption (that is, there exists a cone spanned by a small subset of the columns of the input nonnegative data matrix containing all columns),…

Machine Learning · Statistics 2014-04-07 Nicolas Gillis , Stephen A. Vavasis

An algorithm for computing an analytic function of a matrix $A$ is described. The algorithm is intended for the case where $A$ has some close eigenvalues, and clusters (subsets) of close eigenvalues are separated from each other. This…

Numerical Analysis · Mathematics 2023-12-13 V. G. Kurbatov , I. V. Kurbatova

We introduce novel results for approximate inference on planar graphical models using the loop calculus framework. The loop calculus (Chertkov and Chernyak, 2006b) allows to express the exact partition function Z of a graphical model as a…

Artificial Intelligence · Computer Science 2014-08-12 Vicenc Gomez , Hilbert Kappen , Michael Chertkov

We propose a novel and simple spectral method based on the semi-discrete Fourier transforms to discretize the fractional Laplacian $(-\Delta)^\frac{\alpha}{2}$. Numerical analysis and experiments are provided to study its performance. Our…

Numerical Analysis · Mathematics 2024-06-18 Shiping Zhou , Yanzhi Zhang

In this paper we present an adaptable fast matrix multiplication (AFMM) algorithm, for two nxn dense matrices which computes the product matrix with average complexity Tavg(n) = d1d2n3 with the acknowledgement that the average count is…

Data Structures and Algorithms · Computer Science 2013-08-13 Niraj Kumar Singh , Soubhik Chakraborty , Dheeresh Kumar Mallick

We describe an algorithm to factor sparse multivariate polynomials using O(d) bivariate factorizations where d is the number of variables. This algorithm is implemented in the Giac/Xcas computer algebra system.

Symbolic Computation · Computer Science 2016-11-09 Bernard Parisse

We give an algorithm for reversion of formal power series, based on an efficient way to implement the Lagrange inversion formula. Our algorithm requires $O(n^{1/2}(M(n) + MM(n^{1/2})))$ operations where $M(n)$ and $MM(n)$ are the costs of…

Symbolic Computation · Computer Science 2013-12-03 Fredrik Johansson