{"id":"https://openalex.org/W2965718579","doi":"https://doi.org/10.1609/aaai.v33i01.33013232","title":"Online Learning from Data Streams with Varying Feature Spaces","display_name":"Online Learning from Data Streams with Varying Feature Spaces","publication_year":2019,"publication_date":"2019-07-17","ids":{"openalex":"https://openalex.org/W2965718579","doi":"https://doi.org/10.1609/aaai.v33i01.33013232","mag":"2965718579"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v33i01.33013232","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33013232","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4192/4070","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4192/4070","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5021847817","display_name":"Ege Beyaz\u0131t","orcid":"https://orcid.org/0000-0001-5731-7621"},"institutions":[{"id":"https://openalex.org/I79516672","display_name":"University of Louisiana at Lafayette","ror":"https://ror.org/01x8rc503","country_code":"US","type":"education","lineage":["https://openalex.org/I2799628689","https://openalex.org/I79516672"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ege Beyazit","raw_affiliation_strings":["University of Louisiana at Lafayette"],"affiliations":[{"raw_affiliation_string":"University of Louisiana at Lafayette","institution_ids":["https://openalex.org/I79516672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010829999","display_name":"Jeevithan Alagurajah","orcid":null},"institutions":[{"id":"https://openalex.org/I79516672","display_name":"University of Louisiana at Lafayette","ror":"https://ror.org/01x8rc503","country_code":"US","type":"education","lineage":["https://openalex.org/I2799628689","https://openalex.org/I79516672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeevithan Alagurajah","raw_affiliation_strings":["University of Louisiana at Lafayette"],"affiliations":[{"raw_affiliation_string":"University of Louisiana at Lafayette","institution_ids":["https://openalex.org/I79516672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080738591","display_name":"Xindong Wu","orcid":"https://orcid.org/0000-0003-2396-1704"},"institutions":[{"id":"https://openalex.org/I79516672","display_name":"University of Louisiana at Lafayette","ror":"https://ror.org/01x8rc503","country_code":"US","type":"education","lineage":["https://openalex.org/I2799628689","https://openalex.org/I79516672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xindong Wu","raw_affiliation_strings":["University of Louisiana at Lafayette"],"affiliations":[{"raw_affiliation_string":"University of Louisiana at Lafayette","institution_ids":["https://openalex.org/I79516672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021847817"],"corresponding_institution_ids":["https://openalex.org/I79516672"],"apc_list":null,"apc_paid":null,"fwci":2.7931,"has_fulltext":true,"cited_by_count":53,"citation_normalized_percentile":{"value":0.92047949,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"33","issue":"01","first_page":"3232","last_page":"3239"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9972000122070312,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9972000122070312,"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/T12391","display_name":"Artificial Immune Systems Applications","score":0.9693999886512756,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9332000017166138,"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/feature-vector","display_name":"Feature vector","score":0.7055144309997559},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6599358916282654},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6470737457275391},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6459500193595886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6254213452339172},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5662431716918945},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.5202304720878601},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5165173411369324},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.511282205581665},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4469875991344452},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43960827589035034},{"id":"https://openalex.org/keywords/linear-classifier","display_name":"Linear classifier","score":0.41991856694221497},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3890010416507721}],"concepts":[{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.7055144309997559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6599358916282654},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6470737457275391},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6459500193595886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6254213452339172},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5662431716918945},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.5202304720878601},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5165173411369324},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.511282205581665},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4469875991344452},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43960827589035034},{"id":"https://openalex.org/C139532973","wikidata":"https://www.wikidata.org/wiki/Q2679259","display_name":"Linear classifier","level":3,"score":0.41991856694221497},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3890010416507721},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v33i01.33013232","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33013232","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4192/4070","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v33i01.33013232","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v33i01.33013232","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/4192/4070","source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1539379727","display_name":null,"funder_award_id":"1763620","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7605139725","display_name":null,"funder_award_id":"1652107","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2965718579.pdf","grobid_xml":"https://content.openalex.org/works/W2965718579.grobid-xml"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1762008180","https://openalex.org/W1966771059","https://openalex.org/W1993014433","https://openalex.org/W2012243161","https://openalex.org/W2012715465","https://openalex.org/W2040870580","https://openalex.org/W2059571389","https://openalex.org/W2068714596","https://openalex.org/W2089394015","https://openalex.org/W2104554891","https://openalex.org/W2105867876","https://openalex.org/W2113459411","https://openalex.org/W2126351339","https://openalex.org/W2126561871","https://openalex.org/W2148114066","https://openalex.org/W2150621701","https://openalex.org/W2152793312","https://openalex.org/W2153338628","https://openalex.org/W2161813894","https://openalex.org/W2163046677","https://openalex.org/W2167348934","https://openalex.org/W2244998654","https://openalex.org/W2346780474","https://openalex.org/W2412267538","https://openalex.org/W2521689864","https://openalex.org/W2618378892","https://openalex.org/W2626103914","https://openalex.org/W2950119841","https://openalex.org/W2964252810","https://openalex.org/W3009009611","https://openalex.org/W4292022450","https://openalex.org/W4297790634","https://openalex.org/W6634527986","https://openalex.org/W6641990611","https://openalex.org/W6665408448","https://openalex.org/W6667684292","https://openalex.org/W6673214705","https://openalex.org/W6675682377","https://openalex.org/W6675792869","https://openalex.org/W6676984168","https://openalex.org/W6680187362","https://openalex.org/W6682572403","https://openalex.org/W6683584131","https://openalex.org/W6683812253","https://openalex.org/W6684797212","https://openalex.org/W6690896754","https://openalex.org/W6704789851","https://openalex.org/W6727181731","https://openalex.org/W6733923534","https://openalex.org/W6739308774","https://openalex.org/W6743491589"],"related_works":["https://openalex.org/W3200179079","https://openalex.org/W2324062652","https://openalex.org/W2546942002","https://openalex.org/W2944661354","https://openalex.org/W1983733476","https://openalex.org/W2387099566","https://openalex.org/W3087493185","https://openalex.org/W2254323784","https://openalex.org/W1967062067","https://openalex.org/W1981959369"],"abstract_inverted_index":{"We":[0],"study":[1],"the":[2,86,116,120,130,134,138,151,167,173,176,182,194,210,213,224,237],"problem":[3,12],"of":[4,175,212],"online":[5,18,42,50,97],"learning":[6,19,51,61,98,239],"with":[7,62,105,201,219],"varying":[8,21,78,107,202],"feature":[9,22,44,63,79,87,108,117,123,144,147,157,187,203],"spaces.":[10,109],"The":[11,110,146,159],"is":[13,190],"challenging":[14],"because,":[15],"unlike":[16],"traditional":[17],"problems,":[20],"spaces":[23,80,118,124,204],"can":[24],"introduce":[25],"new":[26],"features":[27,32],"or":[28],"stop":[29],"having":[30],"some":[31],"without":[33],"following":[34,166],"a":[35,95,155,186],"pattern.":[36],"Other":[37],"existing":[38],"methods":[39],"such":[40],"as":[41],"streaming":[43],"selection":[45],"(Wu":[46],"et":[47,57,242],"al.":[48,58,243],"2013),":[49],"from":[52,76,103,122],"trapezoidal":[53,220],"data":[54,104,221],"streams":[55,65,222],"(Zhang":[56,241],"2016),":[59],"and":[60,68,119,137,172],"evolvable":[64],"(Hou,":[66],"Zhang,":[67],"Zhou":[69],"2017)":[70],"are":[71],"not":[72],"capable":[73],"to":[74,101,114,192,208,230],"learn":[75,102],"arbitrarily":[77,106],"because":[81],"they":[82],"make":[83],"assumptions":[84],"about":[85],"space":[88,148],"dynamics.":[89],"In":[90],"this":[91],"paper,":[92],"we":[93],"propose":[94],"novel":[96],"algorithm":[99,112,131,240],"OLVF":[100,111,215,233],"learns":[113],"classify":[115,127],"instances":[121],"simultaneously.":[125],"To":[126],"an":[128],"instance,":[129],"dynamically":[132],"projects":[133],"instance":[135,140,160],"classifier":[136,149,161],"training":[139],"onto":[141],"their":[142],"shared":[143],"subspace.":[145],"predicts":[150],"projection":[152,183],"confidences":[153],"for":[154],"given":[156],"space.":[158],"will":[162,178],"be":[163,179],"updated":[164],"by":[165,181],"empirical":[168],"risk":[169],"minimization":[170],"principle":[171],"strength":[174],"constraints":[177],"scaled":[180],"confidences.":[184],"Afterwards,":[185],"sparsity":[188],"method":[189],"applied":[191],"reduce":[193],"model":[195],"complexity.":[196],"Experiments":[197],"on":[198,223],"10":[199],"datasets":[200,226],"have":[205,227],"been":[206,228],"conducted":[207,229],"demonstrate":[209],"performance":[211],"proposed":[214],"algorithm.":[216],"Moreover,":[217],"experiments":[218],"same":[225],"show":[231],"that":[232],"performs":[234],"better":[235],"than":[236],"state-of-the-art":[238],"2016).":[244]},"counts_by_year":[{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}