Multiplication of 0-1 matrices via clustering

Fuente: arXiv
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Main Authors: Jansson, Jesper, Kowaluk, Miroslaw, Lingas, Andrzej, Persson, Mia
Format: Preprint
Published: 2025
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author Jansson, Jesper
Kowaluk, Miroslaw
Lingas, Andrzej
Persson, Mia
author_facet Jansson, Jesper
Kowaluk, Miroslaw
Lingas, Andrzej
Persson, Mia
contents We study applications of clustering (in particular, the $k$-center clustering problem) in the design of efficient and practical algorithms for computing an approximate and the exact arithmetic matrix product of two 0-1 rectangular matrices with clustered rows or columns, respectively. Our results in part can be regarded as an extension of the clustering-based approach to Boolean square matrix multiplication due to Arslan and Chidri (CSC 2011). First, we provide a simple and efficient deterministic algorithm for approximate matrix product of 0-1 matrices, where the additive error is proportional to the minimum maximum radius in an $\ell$-center clustering of the rows of the first matrix or an $k$-center clustering of the columns of the second matrix. Next, we use the approximation algorithm as a preprocessing after which a query asking for the exact value of an arbitrary entry in the product matrix can be answered in time proportional to the additive error. As a consequence, we obtain a simple deterministic algorithm for the exact matrix product of 0-1 matrices. We also present an improved simple deterministic algorithm for the exact product and in addition, faster analogous randomized algorithms for an approximate and the exact matrix products of 0-1 matrices based on randomized $\ell$ and $k$-center clustering.
format Preprint
id arxiv_https___arxiv_org_abs_2503_19631
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Multiplication of 0-1 matrices via clustering
Jansson, Jesper
Kowaluk, Miroslaw
Lingas, Andrzej
Persson, Mia
Data Structures and Algorithms
F.2.2
F.2.2
We study applications of clustering (in particular, the $k$-center clustering problem) in the design of efficient and practical algorithms for computing an approximate and the exact arithmetic matrix product of two 0-1 rectangular matrices with clustered rows or columns, respectively. Our results in part can be regarded as an extension of the clustering-based approach to Boolean square matrix multiplication due to Arslan and Chidri (CSC 2011). First, we provide a simple and efficient deterministic algorithm for approximate matrix product of 0-1 matrices, where the additive error is proportional to the minimum maximum radius in an $\ell$-center clustering of the rows of the first matrix or an $k$-center clustering of the columns of the second matrix. Next, we use the approximation algorithm as a preprocessing after which a query asking for the exact value of an arbitrary entry in the product matrix can be answered in time proportional to the additive error. As a consequence, we obtain a simple deterministic algorithm for the exact matrix product of 0-1 matrices. We also present an improved simple deterministic algorithm for the exact product and in addition, faster analogous randomized algorithms for an approximate and the exact matrix products of 0-1 matrices based on randomized $\ell$ and $k$-center clustering.
title Multiplication of 0-1 matrices via clustering
topic Data Structures and Algorithms
F.2.2
F.2.2
url https://arxiv.org/abs/2503.19631