Approximation algorithms inspired by kernelization nethods

Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of reduction rules and combinatorial insights. We will expose in this paper a similar strategy for obtaining polynomial-time approximation algorithms. Our method features the use of approximation-pre...

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Main Author: Abu-Khzam, Faisal N. (author)
Other Authors: Bazgan, Cristina (author), Chopin, Morgan (author), Fernau, Henning (author)
Format: conferenceObject
Published: 2017
Online Access:http://hdl.handle.net/10725/5380
http://dx.doi.org/10.1007/978-3-319-13075-0 38
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
http://download.springer.com/static/pdf/606/bok%253A978-3-319-13075-0.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Fbook%2F10.1007%2F978-3-319-13075-0&token2=exp=1489755151~acl=%2Fstatic%2Fpdf%2F606%2Fbok%25253A978-3-319-13075-0.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Fbook%252F10.1007%252F978-3-319-13075-0*~hmac=30221a1c1d93b0118facf97f0ee988f3e7c7a1ccca24556d5cc9b82b58cb3815#page=481
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author Abu-Khzam, Faisal N.
author2 Bazgan, Cristina
Chopin, Morgan
Fernau, Henning
author2_role author
author
author
author_facet Abu-Khzam, Faisal N.
Bazgan, Cristina
Chopin, Morgan
Fernau, Henning
author_role author
dc.creator.none.fl_str_mv Abu-Khzam, Faisal N.
Bazgan, Cristina
Chopin, Morgan
Fernau, Henning
dc.date.none.fl_str_mv 2017-03-17T12:49:17Z
2017-03-17T12:49:17Z
2017-03-17
dc.identifier.none.fl_str_mv http://hdl.handle.net/10725/5380
http://dx.doi.org/10.1007/978-3-319-13075-0 38
Chopin, M., & Fernau, H. (2014, November). Approximation algorithms inspired by kernelization methods. In Algorithms and Computation: 25th International Symposium, ISAAC 2014, Jeonju, Korea, December 15-17, 2014, Proceedings (Vol. 8889, p. 479). Springer.
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
http://download.springer.com/static/pdf/606/bok%253A978-3-319-13075-0.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Fbook%2F10.1007%2F978-3-319-13075-0&token2=exp=1489755151~acl=%2Fstatic%2Fpdf%2F606%2Fbok%25253A978-3-319-13075-0.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Fbook%252F10.1007%252F978-3-319-13075-0*~hmac=30221a1c1d93b0118facf97f0ee988f3e7c7a1ccca24556d5cc9b82b58cb3815#page=481
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Springer
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.title.none.fl_str_mv Approximation algorithms inspired by kernelization nethods
Algorithms and Computation
dc.type.none.fl_str_mv Conference Paper / Proceeding
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
description Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of reduction rules and combinatorial insights. We will expose in this paper a similar strategy for obtaining polynomial-time approximation algorithms. Our method features the use of approximation-preserving reductions, akin to the notion of parameterized reductions. We exemplify this method to obtain the currently best approximation algorithms for Harmless Set, Differential and Multiple Nonblocker, all of them can be considered in the context of securing networks or information propagation
eu_rights_str_mv openAccess
format conferenceObject
id LAURepo_90bf1fd7686f6a5d8ad0252930e4a693
identifier_str_mv Chopin, M., & Fernau, H. (2014, November). Approximation algorithms inspired by kernelization methods. In Algorithms and Computation: 25th International Symposium, ISAAC 2014, Jeonju, Korea, December 15-17, 2014, Proceedings (Vol. 8889, p. 479). Springer.
language_invalid_str_mv en
network_acronym_str LAURepo
network_name_str Lebanese American University repository
oai_identifier_str oai:laur.lau.edu.lb:10725/5380
publishDate 2017
publisher.none.fl_str_mv Springer
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling Approximation algorithms inspired by kernelization nethodsAlgorithms and ComputationAbu-Khzam, Faisal N.Bazgan, CristinaChopin, MorganFernau, HenningKernelization algorithms in the context of Parameterized Complexity are often based on a combination of reduction rules and combinatorial insights. We will expose in this paper a similar strategy for obtaining polynomial-time approximation algorithms. Our method features the use of approximation-preserving reductions, akin to the notion of parameterized reductions. We exemplify this method to obtain the currently best approximation algorithms for Harmless Set, Differential and Multiple Nonblocker, all of them can be considered in the context of securing networks or information propagationN/ASpringer2017-03-17T12:49:17Z2017-03-17T12:49:17Z2017-03-17Conference Paper / Proceedinginfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://hdl.handle.net/10725/5380http://dx.doi.org/10.1007/978-3-319-13075-0 38Chopin, M., & Fernau, H. (2014, November). Approximation algorithms inspired by kernelization methods. In Algorithms and Computation: 25th International Symposium, ISAAC 2014, Jeonju, Korea, December 15-17, 2014, Proceedings (Vol. 8889, p. 479). Springer.http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.phphttp://download.springer.com/static/pdf/606/bok%253A978-3-319-13075-0.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Fbook%2F10.1007%2F978-3-319-13075-0&token2=exp=1489755151~acl=%2Fstatic%2Fpdf%2F606%2Fbok%25253A978-3-319-13075-0.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Fbook%252F10.1007%252F978-3-319-13075-0*~hmac=30221a1c1d93b0118facf97f0ee988f3e7c7a1ccca24556d5cc9b82b58cb3815#page=481eninfo:eu-repo/semantics/openAccessoai:laur.lau.edu.lb:10725/53802021-03-19T10:03:22Z
spellingShingle Approximation algorithms inspired by kernelization nethods
Abu-Khzam, Faisal N.
status_str publishedVersion
title Approximation algorithms inspired by kernelization nethods
title_full Approximation algorithms inspired by kernelization nethods
title_fullStr Approximation algorithms inspired by kernelization nethods
title_full_unstemmed Approximation algorithms inspired by kernelization nethods
title_short Approximation algorithms inspired by kernelization nethods
title_sort Approximation algorithms inspired by kernelization nethods
url http://hdl.handle.net/10725/5380
http://dx.doi.org/10.1007/978-3-319-13075-0 38
http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php
http://download.springer.com/static/pdf/606/bok%253A978-3-319-13075-0.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Fbook%2F10.1007%2F978-3-319-13075-0&token2=exp=1489755151~acl=%2Fstatic%2Fpdf%2F606%2Fbok%25253A978-3-319-13075-0.pdf%3ForiginUrl%3Dhttp%253A%252F%252Flink.springer.com%252Fbook%252F10.1007%252F978-3-319-13075-0*~hmac=30221a1c1d93b0118facf97f0ee988f3e7c7a1ccca24556d5cc9b82b58cb3815#page=481