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Neighborhood-based Strategies for Widening of the Greedy Algorithm of the Set Cover Problem

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Violeta N. Ivanova-RohlingAuthors Info & Claims

CompSysTech '18: Proceedings of the 19th International Conference on Computer Systems and Technologies

Pages 27 - 32

https://doi.org/10.1145/3274005.3274036

Published: 13 September 2018 Publication History

Abstract

We live in the age of ever-increasing parallel computing resources. For a decade there has been intense research into parallel data mining algorithms. Most of this research is focused on improving the running time of existing algorithms. In contrast our focus is the improvement of the solution quality, or model accuracy. We are looking for "smart" strategies to invest parallel compute resources in order to achieve a better exploration of the search space by exploring several solutions in parallel, referred to as Widening. In this paper, we demonstrate the effect of neighborhood-based Widening with different types of neighborhoods for the greedy algorithm of the set cover problem.

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Cited By

Das SChakraborty APapavassiliou SSchmid S(2024)SkySCALE: A Radio Tomographic Approach Towards Scaling UAV Network DeploymentsProceedings of the Twenty-fifth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing10.1145/3641512.3686384(341-350)Online publication date: 14-Oct-2024
https://dl.acm.org/doi/10.1145/3641512.3686384
Ivanova-Rohling VRohling N(2020)Evaluating Machine Learning Approaches for Discovering Optimal Sets of Projection Operators for Quantum State Tomography of Qubit SystemsCybernetics and Information Technologies10.2478/cait-2020-006120:6(61-73)Online publication date: 31-Dec-2020
https://doi.org/10.2478/cait-2020-0061

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cover image ACM Other conferences

CompSysTech '18: Proceedings of the 19th International Conference on Computer Systems and Technologies

September 2018

206 pages

ISBN:9781450364256

DOI:10.1145/3274005

Copyright © 2018 ACM.

© 2018 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

In-Cooperation

ERSVB: EURORISC SYSTEMS - Varna, Bulgaria
FOSEUB: FEDERATION OF THE SCIENTIFIC ENGINEERING UNIONS - Bulgaria
UORB: University of Ruse, Bulgaria
TECHUVB: Technical University of Varna, Bulgaria

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 13 September 2018

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CompSysTech'18

CompSysTech'18: 19th International Conference on Computer Systems and Technologies

September 13 - 14, 2018

Ruse, Bulgaria

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Overall Acceptance Rate 241 of 492 submissions, 49%

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Cited By

Das SChakraborty APapavassiliou SSchmid S(2024)SkySCALE: A Radio Tomographic Approach Towards Scaling UAV Network DeploymentsProceedings of the Twenty-fifth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing10.1145/3641512.3686384(341-350)Online publication date: 14-Oct-2024
https://dl.acm.org/doi/10.1145/3641512.3686384
Ivanova-Rohling VRohling N(2020)Evaluating Machine Learning Approaches for Discovering Optimal Sets of Projection Operators for Quantum State Tomography of Qubit SystemsCybernetics and Information Technologies10.2478/cait-2020-006120:6(61-73)Online publication date: 31-Dec-2020
https://doi.org/10.2478/cait-2020-0061

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