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We present algorithms for the type-IV discrete cosine transform (DCT-IV) and discrete sine transform (DST-IV), as well as for the modified discrete cosine transform (MDCT) and its inverse, that achieve a lower count of real multiplications…

Data Structures and Algorithms · Computer Science 2009-01-29 Xuancheng Shao , Steven G. Johnson

In this overview article we present several methods for multiplying matrices and the implementation of these methods in C. Also a little test program is given to compare their running time and the numerical stability. The methods are: naive…

Mathematical Software · Computer Science 2011-06-08 Ivo Hedtke

We show that the bilinear complexity of multiplication in a non-split quaternion algebra over a field of characteristic distinct from 2 is 8. This question is motivated by the problem of characterising algebras of almost minimal rank…

Computational Complexity · Computer Science 2012-08-29 Vladimir Lysikov

The polynomial multiplication problem has attracted considerable attention since the early days of computer algebra, and several algorithms have been designed to achieve the best possible time complexity. More recently, efforts have been…

Symbolic Computation · Computer Science 2019-02-11 Pascal Giorgi , Bruno Grenet , Daniel Roche

In this paper, an exact algorithm in polynomial time is developed to solve unrestricted binary quadratic programs. The computational complexity is $O\left( n^{\frac{15}{2}}\right) $, although very conservative, it is sufficient to prove…

Data Structures and Algorithms · Computer Science 2021-02-02 Juan Ignacio Mulero-Martínez

We further develop the group-theoretic approach to fast matrix multiplication introduced by Cohn and Umans, and for the first time use it to derive algorithms asymptotically faster than the standard algorithm. We describe several families…

Group Theory · Mathematics 2012-03-15 Henry Cohn , Robert Kleinberg , Balazs Szegedy , Christopher Umans

Advanced optimization algorithms such as Newton method and AdaGrad benefit from second order derivative or second order statistics to achieve better descent directions and faster convergence rates. At their heart, such algorithms need to…

Machine Learning · Computer Science 2022-08-31 Yao Lu , Mehrtash Harandi , Richard Hartley , Razvan Pascanu

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

Quantum-dot cellular automata (QCA) shows promise as a post silicon CMOS, low power computational technology. Nevertheless, to generalize QCA for next-generation digital devices, the ability to implement conventional programmable circuits…

Mesoscale and Nanoscale Physics · Physics 2011-10-10 Joshua D. Wood , P. Douglas Tougaw

We present RXTX, a new algorithm for computing the product of matrix by its transpose $XX^{t}$ for $X\in \mathbb{R}^{n\times m}$. RXTX uses $5\%$ fewer multiplications and $5\%$ fewer operations (additions and multiplications) than…

Data Structures and Algorithms · Computer Science 2025-05-19 Dmitry Rybin , Yushun Zhang , Zhi-Quan Luo

In this paper, we present fast algorithms for the product of two multivariate polynomials in sparse representation. The bit complexity of our algorithms are studied in detail for various types of coefficients, and we derive new complexity…

Data Structures and Algorithms · Computer Science 2009-01-28 Joris van der Hoeven , Grégoire Lecerf

To multiply astronomic matrices using parallel workers subject to straggling, we recommend interleaving checksums with some fast matrix multiplication algorithms. Nesting the parity-checked algorithms, we weave a product code flavor…

Information Theory · Computer Science 2022-01-13 Hsin-Po Wang , Iwan Duursma

A Las Vegas randomized algorithm is given to compute the Smith multipliers for a nonsingular integer matrix $A$, that is, unimodular matrices $U$ and $V$ such that $AV=US$, with $S$ the Smith normal form of $A$. The expected running time of…

Symbolic Computation · Computer Science 2022-09-23 Stavros Birmpilis , George Labahn , Arne Storjohann

In the past few years, successive improvements of the asymptotic complexity of square matrix multiplication have been obtained by developing novel methods to analyze the powers of the Coppersmith-Winograd tensor, a basic construction…

Data Structures and Algorithms · Computer Science 2021-10-05 François Le Gall , Florent Urrutia

Herein we explore a dual tree algorithm for matrix multiplication of $A\in \mathbb{R}^{M\times D}$ and $B\in\mathbb{R}^{D\times N}$, very narrowly effective if the normalized rows of $A$ and columns of $B$, treated as vectors in…

Data Structures and Algorithms · Computer Science 2020-12-11 CNP Slagle , Lance Fortnow

We dispel with "street wisdom" regarding the practical implementation of Strassen's algorithm for matrix-matrix multiplication (DGEMM). Conventional wisdom: it is only practical for very large matrices. Our implementation is practical for…

Mathematical Software · Computer Science 2016-05-05 Jianyu Huang , Tyler M. Smith , Greg M. Henry , Robert A. van de Geijn

We develop several efficient algorithms for the classical \emph{Matrix Scaling} problem, which is used in many diverse areas, from preconditioning linear systems to approximation of the permanent. On an input $n\times n$ matrix $A$, this…

Data Structures and Algorithms · Computer Science 2017-04-10 Zeyuan Allen-Zhu , Yuanzhi Li , Rafael Oliveira , Avi Wigderson

We estimate the Boolean complexity of multiplication of structured matrices by a vector and the solution of nonsingular linear systems of equations with these matrices. We study four basic most popular classes, that is, Toeplitz, Hankel,…

Symbolic Computation · Computer Science 2014-04-21 Victor Y. Pan , Elias Tsigaridas

As it stands, density matrix purification is a powerful tool for linear scaling electronic structure calculations. The convergence is rapid and depends only weakly on the band gap. However, as will be shown in this paper, there is room for…

Computational Physics · Physics 2011-05-11 Emanuel H. Rubensson

We present a new algorithm for fast matrix multiplication using tensor decompositions which have special features. Thanks to these features we obtain exponents lower than what the rank of the tensor decomposition suggests. In particular for…

Symbolic Computation · Computer Science 2026-05-22 Manuel Kauers , Jakob Moosbauer , Isaac Wood
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