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Given a list of N numbers, the maximum can be computed in N iterations. During these N iterations, the maximum gets updated on average as many times as the Nth harmonic number. We first use this fact to approximate the Nth harmonic number…

Data Structures and Algorithms · Computer Science 2017-04-24 Ali Dasdan

Randomized sampling has recently been proven a highly efficient technique for computing approximate factorizations of matrices that have low numerical rank. This paper describes an extension of such techniques to a wider class of matrices…

Numerical Analysis · Mathematics 2015-03-25 Per-Gunnar Martinsson

We consider the problem of preprocessing an $n\times n$ matrix $\mathbf{M}$, and supporting queries that, for any vector $v$, returns the matrix-vector product $\mathbf{M} v$. This problem has been extensively studied in both theory and…

Data Structures and Algorithms · Computer Science 2026-02-10 Emile Anand , Jan van den Brand , Rose McCarty

The $N$th power of a polynomial matrix of fixed size and degree can be computed by binary powering as fast as multiplying two polynomials of linear degree in~$N$. When Fast Fourier Transform (FFT) is available, the resulting complexity is…

Symbolic Computation · Computer Science 2023-05-29 Alin Bostan , Vincent Neiger , Sergey Yurkevich

The quantum Fourier transform (QFT) is a powerful tool in quantum computing. The main ingredients of QFT are formed by the Walsh-Hadamard transform H and phase shifts P(.), both of which are 2x2 unitary matrices as operators on the…

Quantum Physics · Physics 2007-05-23 Charles M. Bowden , Goong Chen , Zijian Diao , Andreas Klappenecker

We explore new approaches for finding matrix multiplication algorithms in the commutative setting by adapting the flip graph technique: a method previously shown to be effective for discovering fast algorithms in the non-commutative case.…

Symbolic Computation · Computer Science 2025-06-30 Isaac Wood

Tensor decompositions, which represent an $N$-order tensor using approximately $N$ factors of much smaller dimensions, can significantly reduce the number of parameters. This is particularly beneficial for high-order tensors, as the number…

Machine Learning · Computer Science 2025-06-23 Zhen Qin , Michael B. Wakin , Zhihui Zhu

The complexity of matrix multiplication is measured in terms of $\omega$, the smallest real number such that two $n\times n$ matrices can be multiplied using $O(n^{\omega+\epsilon})$ field operations for all $\epsilon>0$; the best bound…

Data Structures and Algorithms · Computer Science 2024-09-11 Josh Alman , Virginia Vassilevska Williams

In [1], a new construction called red-black hierarchy characterizing Laman graphs and an algorithm for computing it were presented. For a Laman graph G=(V,E) with n vertices it runs in O(n^2) time assuming that a partition of (V,E+e) into…

Computational Geometry · Computer Science 2008-02-29 Sergey Bereg

Frugal computing is becoming an important topic for environmental reasons. In this context, several techniques have been proposed to reduce the storage of scientific data by dedicated compression methods specially tailored for arrays of…

Data Structures and Algorithms · Computer Science 2022-03-01 Matthieu Martel

We show how to construct highly symmetric algorithms for matrix multiplication. In particular, we consider algorithms which decompose the matrix multiplication tensor into a sum of rank-1 tensors, where the decomposition itself consists of…

Computational Complexity · Computer Science 2016-12-13 Joshua A. Grochow , Cristopher Moore

We show that quantum search can be used to compute the hardness to round an elementary function, that is, to determine the minimum working precision required to compute the values of an elementary function correctly rounded to a target…

Quantum Physics · Physics 2026-01-21 Stefanos Kourtis

We consider the problem of computing the rank of an m x n matrix A over a field. We present a randomized algorithm to find a set of r = rank(A) linearly independent columns in \~O(|A| + r^\omega) field operations, where |A| denotes the…

Data Structures and Algorithms · Computer Science 2015-03-20 Ho Yee Cheung , Tsz Chiu Kwok , Lap Chi Lau

We study the exact counting problem for all lattice rectangles contained in the square $[0,n)\times[0,n)$, including non-axis-parallel ones. Starting from the standard parametrization by a primitive direction $(u,v)$ and two side lengths,…

Computational Geometry · Computer Science 2026-05-04 Dmitry Babichev , Sergey Babichev

We present two new algebraic multilevel hierarchical matrix algorithms to perform fast matrix-vector product (MVP) for $N$-body problems in $d$ dimensions, namely efficient $\mathcal{H}^2_{*}$ (fully nested algorithm, i.e., $\mathcal{H}^2$…

Numerical Analysis · Mathematics 2026-04-13 Ritesh Khan , Sivaram Ambikasaran

We study optimization problems that are neither approximable in polynomial time (at least with a constant factor) nor fixed parameter tractable, under widely believed complexity assumptions. Specifically, we focus on Maximum Independent…

Data Structures and Algorithms · Computer Science 2008-10-29 Marek Cygan , Lukasz Kowalik , Marcin Pilipczuk , Mateusz Wykurz

We present here a new algorithm for the fast computation of N-point correlation functions in large astronomical data sets. The algorithm is based on kdtrees which are decorated with cached sufficient statistics thus allowing for orders of…

A new transform over finite fields, the finite field Hartley transform (FFHT), was recently introduced and a number of promising applications on the design of efficient multiple access systems and multilevel spread spectrum sequences were…

Numerical Analysis · Computer Science 2015-02-06 H. M. de Oliveira , R. G. F. Távora , R. J. Cintra , R. M. Campello de Souza

Polynomial system solving is a classical problem in mathematics with a wide range of applications. This makes its complexity a fundamental problem in computer science. Depending on the context, solving has different meanings. In order to…

Symbolic Computation · Computer Science 2013-07-16 Jean-Charles Faugère , Pierrick Gaudry , Louise Huot , Guénaël Renault

Numerous algorithms are used for nonnegative matrix factorization under the assumption that the matrix is nearly separable. In this paper, we show how to make these algorithms efficient for data matrices that have many more rows than…

Machine Learning · Computer Science 2018-01-08 Austin R. Benson , Jason D. Lee , Bartek Rajwa , David F. Gleich
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