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We revisit the fundamental Boolean Matrix Multiplication (BMM) problem. With the invention of algebraic fast matrix multiplication over 50 years ago, it also became known that BMM can be solved in truly subcubic $O(n^\omega)$ time, where…

Data Structures and Algorithms · Computer Science 2024-05-28 Amir Abboud , Nick Fischer , Zander Kelley , Shachar Lovett , Raghu Meka

We present a new combinatorial algorithm for triangle finding and Boolean matrix multiplication that runs in $\hat{O}(n^3/\log^4 n)$ time, where the $\hat{O}$ notation suppresses poly(loglog) factors. This improves the previous best…

Data Structures and Algorithms · Computer Science 2015-05-27 Huacheng Yu

In recent years it has become popular to study dynamic problems in a sensitivity setting: Instead of allowing for an arbitrary sequence of updates, the sensitivity model only allows to apply batch updates of small size to the original input…

Data Structures and Algorithms · Computer Science 2017-03-07 Monika Henzinger , Andrea Lincoln , Stefan Neumann , Virginia Vassilevska Williams

A tight lower bound for required I/O when computing an ordinary matrix-matrix multiplication on a processor with two layers of memory is established. Prior work obtained weaker lower bounds by reasoning about the number of segments needed…

Computational Complexity · Computer Science 2019-02-07 Tyler Michael Smith , Bradley Lowery , Julien Langou , Robert A. van de Geijn

Karppa & Kaski (2019) proposed a novel ``broken" or ``opportunistic" matrix multiplication algorithm, based on a variant of Strassen's algorithm, and used this to develop new algorithms for Boolean matrix multiplication, among other tasks.…

Data Structures and Algorithms · Computer Science 2024-09-05 David G. Harris

Computing the simulation preorder of a given Kripke structure (i.e., a directed graph with $n$ labeled vertices) has crucial applications in model checking of temporal logic. It amounts to solving a specific two-players reachability game,…

Computational Complexity · Computer Science 2016-08-31 Massimo Cairo , Romeo Rizzi

The quantum query complexity of Boolean matrix multiplication is typically studied as a function of the matrix dimension, n, as well as the number of 1s in the output, \ell. We prove an upper bound of O (n\sqrt{\ell}) for all values of…

Quantum Physics · Physics 2014-12-17 Stacey Jeffery , Robin Kothari , Frédéric Magniez

Maximum bipartite matching (MBM) is a fundamental problem in combinatorial optimization with a long and rich history. A classic result of Hopcroft and Karp (1973) provides an $O(m \sqrt{n})$-time algorithm for the problem, where $n$ and $m$…

Data Structures and Algorithms · Computer Science 2024-06-03 Julia Chuzhoy , Sanjeev Khanna

We propose a new approach to combine Restricted Boltzmann Machines (RBMs) that can be used to solve combinatorial optimization problems. This allows synthesis of larger models from smaller RBMs that have been pretrained, thus effectively…

Machine Learning · Computer Science 2019-09-10 Saavan Patel , Sayeef Salahuddin

We consider the Online Boolean Matrix-Vector Multiplication (OMV) problem studied by Henzinger et al. [STOC'15]: given an $n \times n$ Boolean matrix $M$, we receive $n$ Boolean vectors $v_1,\ldots,v_n$ one at a time, and are required to…

Data Structures and Algorithms · Computer Science 2016-05-09 Kasper Green Larsen , Ryan Williams

The Boolean product $R = P \cdot Q$ of two $\{ 0, 1\} \; m \times m \; $ matrices is $$R(j,k) = 1 \; \mathrm{\ IF\ for\ some\ } \; t \; \,P(j, t) = Q(t, k) = 1\; \; \mathrm{ELSE\ } \, R(j, k) = 0. $$ The near-optimal design reduces the…

Combinatorics · Mathematics 2018-08-27 Eli Shamir

The main theme of this paper is using $k$-dimensional generalizations of the combinatorial Boolean Matrix Multiplication (BMM) hypothesis and the closely-related Online Matrix Vector Multiplication (OMv) hypothesis to prove new tight…

Computational Complexity · Computer Science 2022-02-24 Ce Jin , Yinzhan Xu

This paper presents a quantum algorithm that computes the product of two $n\times n$ Boolean matrices in $\tilde O(n\sqrt{\ell}+\ell\sqrt{n})$ time, where $\ell$ is the number of non-zero entries in the product. This improves the previous…

Quantum Physics · Physics 2021-10-05 François Le Gall

Restricted Boltzmann Machines (RBMs) are a common family of undirected graphical models with latent variables. An RBM is described by a bipartite graph, with all observed variables in one layer and all latent variables in the other. We…

Machine Learning · Computer Science 2020-10-20 Guy Bresler , Rares-Darius Buhai

This paper presents the first combinatorial polynomial-time algorithm for minimizing submodular set functions, answering an open question posed in 1981 by Grotschel, Lovasz, and Schrijver. The algorithm employs a scaling scheme that uses a…

Combinatorics · Mathematics 2007-05-23 Satoru Iwata , Lisa Fleischer , Satoru Fujishige

Inclusion-based (i.e., Andersen-style) points-to analysis is a fundamental static analysis problem. The seminal work of Andersen gave a worst-case cubic $O(n^3)$ time points-to analysis algorithm for C, where $n$ is proportional to the…

Programming Languages · Computer Science 2021-01-05 Qirun Zhang

We prove lower bounds on complexity measures, such as the approximate degree of a Boolean function and the approximate rank of a Boolean matrix, using quantum arguments. We prove these lower bounds using a quantum query algorithm for the…

Quantum Physics · Physics 2018-07-18 Shalev Ben-David , Adam Bouland , Ankit Garg , Robin Kothari

We consider the problem of coloring a 3-colorable graph in polynomial time using as few colors as possible. We present a combinatorial algorithm getting down to $\tO(n^{4/11})$ colors. This is the first combinatorial improvement of Blum's…

Discrete Mathematics · Computer Science 2012-05-08 Ken-ichi Kawarabayashi , Mikkel Thorup

Boolean matrix factorization (BMF) approximates a given binary input matrix as the product of two smaller binary factors. Unlike binary matrix factorization based on standard arithmetic, BMF employs the Boolean OR and AND operations for the…

Information Retrieval · Computer Science 2025-12-05 Christos Kolomvakis , Thomas Bobille , Arnaud Vandaele , Nicolas Gillis

Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled. Restricted Boltzmann Machines (RBMs) are generative neural networks with these desired properties. We integrate an…

Neural and Evolutionary Computing · Computer Science 2014-12-01 Malte Probst , Franz Rothlauf , Jörn Grahl
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