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Duan, Wu and Zhou (FOCS 2023) recently obtained the improved upper bound on the exponent of square matrix multiplication $\omega<2.3719$ by introducing a new approach to quantify and compensate the ``combination loss" in prior analyses of…

Data Structures and Algorithms · Computer Science 2023-12-29 François Le Gall

We study the algorithmic problem of multiplying large matrices that are rectangular. We prove that the method that has been used to construct the fastest algorithms for rectangular matrix multiplication cannot give algorithms with…

Computational Complexity · Computer Science 2025-11-10 Matthias Christandl , François Le Gall , Vladimir Lysikov , Jeroen Zuiddam

Fast matrix multiplication is one of the most fundamental problems in algorithm research. The exponent of the optimal time complexity of matrix multiplication is usually denoted by $\omega$. This paper discusses new ideas for improving the…

Data Structures and Algorithms · Computer Science 2023-11-29 Ran Duan , Hongxun Wu , Renfei Zhou

This paper presents a method to analyze the powers of a given trilinear form (a special kind of algebraic constructions also called a tensor) and obtain upper bounds on the asymptotic complexity of matrix multiplication. Compared with…

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

Let {\alpha} be the maximal value such that the product of an n x n^{\alpha} matrix by an n^{\alpha} x n matrix can be computed with n^{2+o(1)} arithmetic operations. In this paper we show that \alpha>0.30298, which improves the previous…

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

Determining the asymptotic algebraic complexity of matrix multiplication, succinctly represented by the matrix multiplication exponent $\omega$, is a central problem in algebraic complexity theory. The best upper bounds on $\omega$, leading…

Computational Complexity · Computer Science 2022-03-08 Matthias Christandl , Péter Vrana , Jeroen Zuiddam

Until a few years ago, the fastest known matrix multiplication algorithm, due to Coppersmith and Winograd (1990), ran in time $O(n^{2.3755})$. Recently, a surge of activity by Stothers, Vassilevska-Williams, and Le Gall has led to an…

Computational Complexity · Computer Science 2021-10-05 Andris Ambainis , Yuval Filmus , François Le Gall

We study the known techniques for designing Matrix Multiplication algorithms. The two main approaches are the Laser method of Strassen, and the Group theoretic approach of Cohn and Umans. We define a generalization based on zeroing outs…

Computational Complexity · Computer Science 2018-10-23 Josh Alman , Virginia Vassilevska Williams

We determine the border ranks of tensors that could potentially advance the known upper bound for the exponent $\omega$ of matrix multiplication. The Kronecker square of the small $q=2$ Coppersmith-Winograd tensor equals the $3\times 3$…

Algebraic Geometry · Mathematics 2020-09-25 Austin Conner , Hang Huang , J. M. Landsberg

In this work, we prove limitations on the known methods for designing matrix multiplication algorithms. Alman and Vassilevska Williams recently defined the Universal Method, which substantially generalizes all the known approaches including…

Computational Complexity · Computer Science 2019-05-02 Josh Alman

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

We prove that the border rank of the Kronecker square of the little Coppersmith-Winograd tensor $T_{cw,q}$ is the square of its border rank for $q > 2$ and that the border rank of its Kronecker cube is the cube of its border rank for $q >…

Computational Complexity · Computer Science 2021-12-28 Austin Conner , Fulvio Gesmundo , Joseph M. Landsberg , Emanuele Ventura

In a paper published in 1981, Sch\"onhage showed that large total matrix multiplications can be reduced to powers of partial matrix multiplication tensors, which correspond to the bilinear computation task of multiplying matrices with some…

Computational Complexity · Computer Science 2024-08-29 Péter Vrana

An important building block in all current asymptotically fast algorithms for matrix multiplication are tensors with low border rank, that is, tensors whose border rank is equal or very close to their size. To find new asymptotically fast…

Computational Complexity · Computer Science 2016-08-25 Markus Bläser , Vladimir Lysikov

We consider the techniques behind the current best algorithms for matrix multiplication. Our results are threefold. (1) We provide a unifying framework, showing that all known matrix multiplication running times since 1986 can be achieved…

Computational Complexity · Computer Science 2017-12-21 Josh Alman , Virginia Vassilevska Williams

Algebraic matrix multiplication algorithms are designed by bounding the rank of matrix multiplication tensors, and then using a recursive method. However, designing algorithms in this way quickly leads to large constant factors: if one…

Computational Complexity · Computer Science 2024-10-29 Josh Alman , Hantao Yu

We present a new improvement on the laser method for designing fast matrix multiplication algorithms. The new method further develops the recent advances by [Duan, Wu, Zhou FOCS 2023] and [Vassilevska Williams, Xu, Xu, Zhou SODA 2024].…

Data Structures and Algorithms · Computer Science 2024-10-22 Josh Alman , Ran Duan , Virginia Vassilevska Williams , Yinzhan Xu , Zixuan Xu , Renfei Zhou

The Strassen algorithm and Winograd's variant accelerate matrix multiplication by using fewer arithmetic operations than standard matrix multiplication. Although many papers have been published to accelerate single- as well as…

Numerical Analysis · Mathematics 2015-10-27 Tomonori Kouya

After Strassen presented the first sub-cubic matrix multiplication algorithm, many Strassen-like algorithms are presented. Most of them with low asymptotic cost have large hidden leading coefficient which are thus impractical. To reduce the…

Symbolic Computation · Computer Science 2022-03-31 Pu Wu , Huiqing Jiang , Zehui Shao , Jin Xu

It is known that the multiplication of an $N \times M$ matrix with an $M \times P$ matrix can be performed using fewer multiplications than what the naive $NMP$ approach suggests. The most famous instance of this is Strassen's algorithm for…

Artificial Intelligence · Computer Science 2023-07-18 Arnaud Deza , Chang Liu , Pashootan Vaezipoor , Elias B. Khalil
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