{"id":"https://openalex.org/W2147315144","doi":"https://doi.org/10.1109/ijcnn.2009.5178618","title":"A fast SVM training method for very large datasets","display_name":"A fast SVM training method for very large datasets","publication_year":2009,"publication_date":"2009-06-01","ids":{"openalex":"https://openalex.org/W2147315144","doi":"https://doi.org/10.1109/ijcnn.2009.5178618","mag":"2147315144"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2009.5178618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","raw_type":"proceedings-article"},"type":"article","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/A5100732746","display_name":"Boyang Li","orcid":"https://orcid.org/0000-0002-6230-2376"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Boyang Li","raw_affiliation_strings":["Graduate School of Information, Production and Systems, Waseda University, Fukuoka, Japan","Graduate School of Information, Production and Systems, Waseda University, Hibikino 2\u20107, Wakamatsu\u2010ku, Kitakyushu\u2010shi, Fukuoka\u2010ken, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Fukuoka, Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Hibikino 2\u20107, Wakamatsu\u2010ku, Kitakyushu\u2010shi, Fukuoka\u2010ken, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101570146","display_name":"Qiangwei Wang","orcid":"https://orcid.org/0000-0002-7308-049X"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Qiangwei Wang","raw_affiliation_strings":["Graduate School of Information, Production and Systems, Waseda University, Fukuoka, Japan","Graduate School of Information, Production and Systems, Waseda University, Hibikino 2\u20107, Wakamatsu\u2010ku, Kitakyushu\u2010shi, Fukuoka\u2010ken, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Fukuoka, Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Hibikino 2\u20107, Wakamatsu\u2010ku, Kitakyushu\u2010shi, Fukuoka\u2010ken, Japan","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100326923","display_name":"Jinglu Hu","orcid":"https://orcid.org/0000-0002-5601-7261"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jinglu Hu","raw_affiliation_strings":["Graduate School of Information, Production and Systems, Waseda University, Fukuoka, Japan","Graduate School of Information, Production and Systems, Waseda University, Hibikino 2\u20107, Wakamatsu\u2010ku, Kitakyushu\u2010shi, Fukuoka\u2010ken, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Fukuoka, Japan","institution_ids":["https://openalex.org/I150744194"]},{"raw_affiliation_string":"Graduate School of Information, Production and Systems, Waseda University, Hibikino 2\u20107, Wakamatsu\u2010ku, Kitakyushu\u2010shi, Fukuoka\u2010ken, Japan","institution_ids":["https://openalex.org/I150744194"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9709,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.88439565,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1784","last_page":"1789"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9966999888420105,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9966999888420105,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9900000095367432,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9894999861717224,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7912644743919373},{"id":"https://openalex.org/keywords/centroid","display_name":"Centroid","score":0.7663114070892334},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6952089071273804},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6347958445549011},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6165992617607117},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5827083587646484},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5689842104911804},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.5261496901512146},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4817885756492615},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3568122982978821},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2844063639640808}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7912644743919373},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.7663114070892334},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6952089071273804},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6347958445549011},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6165992617607117},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5827083587646484},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5689842104911804},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5261496901512146},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4817885756492615},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3568122982978821},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2844063639640808},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2009.5178618","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2009.5178618","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 International Joint Conference on Neural Networks","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W184442817","https://openalex.org/W1496317909","https://openalex.org/W1499677203","https://openalex.org/W1514940655","https://openalex.org/W1551209770","https://openalex.org/W1621799579","https://openalex.org/W1869391892","https://openalex.org/W2052564542","https://openalex.org/W2068405010","https://openalex.org/W2097998671","https://openalex.org/W2125126592","https://openalex.org/W2126481981","https://openalex.org/W2137557016","https://openalex.org/W2144414190","https://openalex.org/W2148980227","https://openalex.org/W2155319834","https://openalex.org/W2156860509","https://openalex.org/W2158078575","https://openalex.org/W2172039283","https://openalex.org/W4285719527","https://openalex.org/W4301501800","https://openalex.org/W6607466906","https://openalex.org/W6629644485","https://openalex.org/W6630965568","https://openalex.org/W6632758585","https://openalex.org/W6639165917","https://openalex.org/W6680634009","https://openalex.org/W6681291431","https://openalex.org/W6683152347","https://openalex.org/W6683383647","https://openalex.org/W6989746565"],"related_works":["https://openalex.org/W2381926679","https://openalex.org/W2007009951","https://openalex.org/W2082644203","https://openalex.org/W2350539780","https://openalex.org/W3165040664","https://openalex.org/W3122652148","https://openalex.org/W1583866266","https://openalex.org/W4242386713","https://openalex.org/W2996505764","https://openalex.org/W3088649123"],"abstract_inverted_index":{"In":[0,83],"a":[1,88,109,144],"standard":[2],"support":[3,60],"vector":[4],"machine":[5],"(SVM),":[6],"the":[7,28,43,67,75,92,102,117,128,136,148,156],"training":[8,31,46,137,141,149],"process":[9,150],"has":[10],"O(n":[11,18],"<sup":[12,19],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[13,20],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">3</sup>":[14],")":[15,22],"time":[16],"and":[17,127],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[21],"space":[23],"complexities,":[24],"where":[25],"n":[26],"is":[27,35,48],"size":[29,44,146],"of":[30,45,119,130],"dataset.":[32,138],"Thus,":[33],"it":[34],"computationally":[36],"infeasible":[37],"for":[38],"very":[39],"large":[40],"datasets.":[41],"Reducing":[42],"dataset":[47,142],"naturally":[49],"considered":[50],"to":[51,66,73,80,96,115,134],"solve":[52],"this":[53,84],"problem.":[54],"SVM":[55],"classifiers":[56],"depend":[57],"on":[58,91],"only":[59],"vectors":[61],"(SVs)":[62],"that":[63,77],"lie":[64],"close":[65],"separation":[68],"boundary.":[69],"Therefore,":[70],"we":[71,86,106],"need":[72],"reserve":[74],"samples":[76,122],"are":[78,132],"likely":[79],"be":[81],"SVs.":[82],"paper,":[85],"propose":[87],"method":[89],"based":[90],"edge":[93,125],"detection":[94],"technique":[95],"detect":[97],"these":[98],"samples.":[99],"To":[100],"preserve":[101],"entire":[103],"distribution":[104],"properties,":[105],"also":[107],"use":[108],"clustering":[110],"algorithm":[111],"such":[112],"as":[113],"K-means":[114],"calculate":[116],"centroids":[118,129],"clusters.":[120],"The":[121,139],"selected":[123],"by":[124],"detector":[126],"clusters":[131],"used":[133],"reconstruct":[135],"reconstructed":[140],"with":[143],"smaller":[145],"makes":[147],"much":[151],"faster,":[152],"but":[153],"without":[154],"degrading":[155],"classification":[157],"accuracies.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
