Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set

Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Nature machine intelligence 2023-01, Vol.5 (1), p.29-31
Hauptverfasser: Angelini, Maria Chiara, Ricci-Tersenghi, Federico
Format: Artikel
Sprache:eng
Schlagworte:
639/705/117
639/766/530/2801
Algorithms
Approximation
Benchmarks
Combinatorial analysis
Engineering
Graph neural networks
Greedy algorithms
Matters Arising
Neural networks
Optimization
Physics
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 31
container_issue 1
container_start_page 29
container_title Nature machine intelligence
container_volume 5
creator Angelini, Maria Chiara
Ricci-Tersenghi, Federico
description
doi_str_mv 10.1038/s42256-022-00589-y
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2768952316</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2768952316</sourcerecordid><originalsourceid>FETCH-LOGICAL-c319t-7ad7490229252888ca05848219d3c82cbffb8dae4bede19fac5ad3ef9318f5b93</originalsourceid><addsrcrecordid>eNp9kMtO5DAQRSME0iDgB2ZliXXAj6TbXiLES-oRm2FtOXYlbUjsYLuBns-YL6agR4LVbFxl-dxy3VtVPxk9Y1TI89xw3i5qynlNaStVvd2rDnmL11YKtf-t_1Gd5PxIKeWsaVraHFZ_f0UHKZAhmXlNAmySGbGU15ieMnGRYJOBlLUJxI4mZ28RGBKA2xIzDjH5sp4y8YHkOL74MBAbp84HU_AJ0TgXP_k_pvgYyJxiNwLio38CMpk3P20m1DqYAY9QSIZyXB30Zsxw8q8eVQ_XV78vb-vV_c3d5cWqtoKpUi-NWzYKTSu0J6W0Br03kjPlhJXcdn3fSWeg6cABU72xrXECeiWY7NtOiaPqdDcXt3reQC76MW5SwC81Xy6karlgC6T4jrIp5pyg13Pyk0lbzaj-iF_v4te4if6MX29RJHaijHAYIH2N_o_qHUd0jXk</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2768952316</pqid></control><display><type>article</type><title>Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set</title><source>SpringerLink Journals - AutoHoldings</source><creator>Angelini, Maria Chiara ; Ricci-Tersenghi, Federico</creator><creatorcontrib>Angelini, Maria Chiara ; Ricci-Tersenghi, Federico</creatorcontrib><identifier>ISSN: 2522-5839</identifier><identifier>EISSN: 2522-5839</identifier><identifier>DOI: 10.1038/s42256-022-00589-y</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>639/705/117 ; 639/766/530/2801 ; Algorithms ; Approximation ; Benchmarks ; Combinatorial analysis ; Engineering ; Graph neural networks ; Greedy algorithms ; Matters Arising ; Neural networks ; Optimization ; Physics</subject><ispartof>Nature machine intelligence, 2023-01, Vol.5 (1), p.29-31</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Limited 2022</rights><rights>The Author(s), under exclusive licence to Springer Nature Limited 2022.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-7ad7490229252888ca05848219d3c82cbffb8dae4bede19fac5ad3ef9318f5b93</citedby><cites>FETCH-LOGICAL-c319t-7ad7490229252888ca05848219d3c82cbffb8dae4bede19fac5ad3ef9318f5b93</cites><orcidid>0000-0002-6277-359X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/s42256-022-00589-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/s42256-022-00589-y$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Angelini, Maria Chiara</creatorcontrib><creatorcontrib>Ricci-Tersenghi, Federico</creatorcontrib><title>Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set</title><title>Nature machine intelligence</title><addtitle>Nat Mach Intell</addtitle><subject>639/705/117</subject><subject>639/766/530/2801</subject><subject>Algorithms</subject><subject>Approximation</subject><subject>Benchmarks</subject><subject>Combinatorial analysis</subject><subject>Engineering</subject><subject>Graph neural networks</subject><subject>Greedy algorithms</subject><subject>Matters Arising</subject><subject>Neural networks</subject><subject>Optimization</subject><subject>Physics</subject><issn>2522-5839</issn><issn>2522-5839</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9kMtO5DAQRSME0iDgB2ZliXXAj6TbXiLES-oRm2FtOXYlbUjsYLuBns-YL6agR4LVbFxl-dxy3VtVPxk9Y1TI89xw3i5qynlNaStVvd2rDnmL11YKtf-t_1Gd5PxIKeWsaVraHFZ_f0UHKZAhmXlNAmySGbGU15ieMnGRYJOBlLUJxI4mZ28RGBKA2xIzDjH5sp4y8YHkOL74MBAbp84HU_AJ0TgXP_k_pvgYyJxiNwLio38CMpk3P20m1DqYAY9QSIZyXB30Zsxw8q8eVQ_XV78vb-vV_c3d5cWqtoKpUi-NWzYKTSu0J6W0Br03kjPlhJXcdn3fSWeg6cABU72xrXECeiWY7NtOiaPqdDcXt3reQC76MW5SwC81Xy6karlgC6T4jrIp5pyg13Pyk0lbzaj-iF_v4te4if6MX29RJHaijHAYIH2N_o_qHUd0jXk</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Angelini, Maria Chiara</creator><creator>Ricci-Tersenghi, Federico</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M2P</scope><scope>P5Z</scope><scope>P62</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0002-6277-359X</orcidid></search><sort><creationdate>20230101</creationdate><title>Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set</title><author>Angelini, Maria Chiara ; Ricci-Tersenghi, Federico</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-7ad7490229252888ca05848219d3c82cbffb8dae4bede19fac5ad3ef9318f5b93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>639/705/117</topic><topic>639/766/530/2801</topic><topic>Algorithms</topic><topic>Approximation</topic><topic>Benchmarks</topic><topic>Combinatorial analysis</topic><topic>Engineering</topic><topic>Graph neural networks</topic><topic>Greedy algorithms</topic><topic>Matters Arising</topic><topic>Neural networks</topic><topic>Optimization</topic><topic>Physics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Angelini, Maria Chiara</creatorcontrib><creatorcontrib>Ricci-Tersenghi, Federico</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Science Database</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>Nature machine intelligence</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Angelini, Maria Chiara</au><au>Ricci-Tersenghi, Federico</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set</atitle><jtitle>Nature machine intelligence</jtitle><stitle>Nat Mach Intell</stitle><date>2023-01-01</date><risdate>2023</risdate><volume>5</volume><issue>1</issue><spage>29</spage><epage>31</epage><pages>29-31</pages><issn>2522-5839</issn><eissn>2522-5839</eissn><cop>London</cop><pub>Nature Publishing Group UK</pub><doi>10.1038/s42256-022-00589-y</doi><tpages>3</tpages><orcidid>https://orcid.org/0000-0002-6277-359X</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 2522-5839
ispartof Nature machine intelligence, 2023-01, Vol.5 (1), p.29-31
issn 2522-5839
2522-5839
language eng
recordid cdi_proquest_journals_2768952316
source SpringerLink Journals - AutoHoldings
subjects 639/705/117
639/766/530/2801
Algorithms
Approximation
Benchmarks
Combinatorial analysis
Engineering
Graph neural networks
Greedy algorithms
Matters Arising
Neural networks
Optimization
Physics
title Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T11%3A41%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Modern%20graph%20neural%20networks%20do%20worse%20than%20classical%20greedy%20algorithms%20in%20solving%20combinatorial%20optimization%20problems%20like%20maximum%20independent%20set&rft.jtitle=Nature%20machine%20intelligence&rft.au=Angelini,%20Maria%20Chiara&rft.date=2023-01-01&rft.volume=5&rft.issue=1&rft.spage=29&rft.epage=31&rft.pages=29-31&rft.issn=2522-5839&rft.eissn=2522-5839&rft_id=info:doi/10.1038/s42256-022-00589-y&rft_dat=%3Cproquest_cross%3E2768952316%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2768952316&rft_id=info:pmid/&rfr_iscdi=true