{"id":"https://openalex.org/W1997007937","doi":"https://doi.org/10.1145/1553374.1553421","title":"Fast evolutionary maximum margin clustering","display_name":"Fast evolutionary maximum margin clustering","publication_year":2009,"publication_date":"2009-06-14","ids":{"openalex":"https://openalex.org/W1997007937","doi":"https://doi.org/10.1145/1553374.1553421","mag":"1997007937"},"language":"en","primary_location":{"id":"doi:10.1145/1553374.1553421","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1553374.1553421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th Annual International Conference on Machine Learning","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023532714","display_name":"Fabian Gieseke","orcid":"https://orcid.org/0000-0001-7093-5803"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Fabian Gieseke","raw_affiliation_strings":["TU Dortmund, Germany","TU Dortmund, Germany#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]},{"raw_affiliation_string":"TU Dortmund, Germany#TAB#","institution_ids":["https://openalex.org/I200332995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021993986","display_name":"Tapio Pahikkala","orcid":"https://orcid.org/0000-0003-4183-2455"},"institutions":[{"id":"https://openalex.org/I155660961","display_name":"University of Turku","ror":"https://ror.org/05vghhr25","country_code":"FI","type":"education","lineage":["https://openalex.org/I155660961"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Tapio Pahikkala","raw_affiliation_strings":["University of Turku, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Turku, Finland","institution_ids":["https://openalex.org/I155660961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103020462","display_name":"Oliver Kr\u00e4mer","orcid":"https://orcid.org/0000-0001-7607-1700"},"institutions":[{"id":"https://openalex.org/I200332995","display_name":"TU Dortmund University","ror":"https://ror.org/01k97gp34","country_code":"DE","type":"education","lineage":["https://openalex.org/I200332995"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Oliver Kramer","raw_affiliation_strings":["TU Dortmund, Germany","TU Dortmund, Germany#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TU Dortmund, Germany","institution_ids":["https://openalex.org/I200332995"]},{"raw_affiliation_string":"TU Dortmund, Germany#TAB#","institution_ids":["https://openalex.org/I200332995"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"361","last_page":"368"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11975","display_name":"Evolutionary Algorithms and Applications","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8484784364700317},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.808907151222229},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7138644456863403},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.6297361254692078},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.5631564855575562},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5453594923019409},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.47067791223526},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4327124357223511},{"id":"https://openalex.org/keywords/constrained-clustering","display_name":"Constrained clustering","score":0.426988810300827},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3763410747051239},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.3594062924385071},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3315831124782562},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33156853914260864},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2266388237476349}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8484784364700317},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.808907151222229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7138644456863403},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.6297361254692078},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.5631564855575562},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5453594923019409},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.47067791223526},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4327124357223511},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.426988810300827},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3763410747051239},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.3594062924385071},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3315831124782562},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33156853914260864},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2266388237476349},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1553374.1553421","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1553374.1553421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th Annual International Conference on Machine Learning","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.158.1110","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.158.1110","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.mcgill.ca/~icml2009/papers/245.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W155032588","https://openalex.org/W158976495","https://openalex.org/W1494019289","https://openalex.org/W1540155273","https://openalex.org/W1576660662","https://openalex.org/W1596717185","https://openalex.org/W1698155719","https://openalex.org/W1971784203","https://openalex.org/W1977556410","https://openalex.org/W2011665458","https://openalex.org/W2068062841","https://openalex.org/W2108282816","https://openalex.org/W2115245664","https://openalex.org/W2132820034","https://openalex.org/W2136518509","https://openalex.org/W2148603752","https://openalex.org/W2149982386","https://openalex.org/W2153635508","https://openalex.org/W2241799117","https://openalex.org/W2319660501","https://openalex.org/W2798909945","https://openalex.org/W3120421331","https://openalex.org/W6679854563","https://openalex.org/W6750968397","https://openalex.org/W6770641979","https://openalex.org/W6792841710","https://openalex.org/W7071374342"],"related_works":["https://openalex.org/W3146523624","https://openalex.org/W2160785859","https://openalex.org/W1525022337","https://openalex.org/W2188840951","https://openalex.org/W2171583777","https://openalex.org/W2186905933","https://openalex.org/W2969974905","https://openalex.org/W2040929534","https://openalex.org/W2555816786","https://openalex.org/W2390610678"],"abstract_inverted_index":{"The":[0],"maximum":[1],"margin":[2,39],"clustering":[3,19,102],"approach":[4,95],"is":[5,50],"a":[6,42,46,54,67],"recently":[7],"proposed":[8],"extension":[9],"of":[10,13,30,45,87,101],"the":[11,18,31,38,85],"concept":[12],"support":[14,47],"vector":[15,48],"machines":[16],"to":[17,60],"problem.":[20,65],"Briefly":[21],"stated,":[22],"it":[23],"aims":[24],"at":[25],"finding":[26],"an":[27,79],"optimal":[28],"partition":[29],"data":[32,75],"into":[33],"two":[34],"classes":[35],"such":[36],"that":[37,93],"induced":[40],"by":[41],"subsequent":[43],"application":[44],"machine":[49],"maximal.":[51],"We":[52],"propose":[53],"method":[55],"based":[56],"on":[57],"stochastic":[58],"search":[59],"address":[61],"this":[62],"hard":[63],"optimization":[64],"While":[66],"direct":[68],"implementation":[69],"would":[70],"be":[71],"infeasible":[72],"for":[73,83],"large":[74],"sets,":[76],"we":[77],"present":[78],"efficient":[80],"computational":[81],"shortcut":[82],"assessing":[84],"\"quality\"":[86],"intermediate":[88],"solutions.":[89],"Experimental":[90],"results":[91],"show":[92],"our":[94],"outperforms":[96],"existing":[97],"methods":[98],"in":[99],"terms":[100],"accuracy.":[103]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
