Pushing the online matrix-vector conjecture off-line and identifying its easy cases

Leszek Gąsieniec, Jesper Jansson, Christos Levcopoulos, Andrzej Lingas, Mia Persson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Henzinger et al. posed the so called Online Boolean Matrix-vector Multiplication (OMv) conjecture and showed that it implies tight hardness results for several basic partially dynamic or dynamic problems [STOC’15]. We show that the OMv conjecture is implied by a simple off-line conjecture. If a not uniform (i.e., it might be different for different matrices) polynomial-time preprocessing of the matrix in the OMv conjecture is allowed then we can show such a variant of the OMv conjecture to be equivalent to our off-line conjecture. On the other hand, we show that the OMV conjecture does not hold in the restricted cases when the rows of the matrix or the input vectors are clustered.

Original languageEnglish (US)
Title of host publicationFrontiers in Algorithmics - 13th International Workshop, FAW 2019, Proceedings
EditorsMei Lu, Xiaotie Deng, Yijia Chen
PublisherSpringer Verlag
Pages156-169
Number of pages14
ISBN (Print)9783030181253
DOIs
StatePublished - Jan 1 2019
Externally publishedYes
Event13th International Workshop on Frontiers in Algorithmics, FAW 2019 - Sanya, China
Duration: Apr 29 2019May 3 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11458 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Workshop on Frontiers in Algorithmics, FAW 2019
CountryChina
CitySanya
Period4/29/195/3/19

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Gąsieniec, L., Jansson, J., Levcopoulos, C., Lingas, A., & Persson, M. (2019). Pushing the online matrix-vector conjecture off-line and identifying its easy cases. In M. Lu, X. Deng, & Y. Chen (Eds.), Frontiers in Algorithmics - 13th International Workshop, FAW 2019, Proceedings (pp. 156-169). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11458 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-18126-0_14