{"id":"https://openalex.org/W4366238713","doi":"https://doi.org/10.1109/tnnls.2023.3265524","title":"IWDA: Importance Weighting for Drift Adaptation in Streaming Supervised Learning Problems","display_name":"IWDA: Importance Weighting for Drift Adaptation in Streaming Supervised Learning Problems","publication_year":2023,"publication_date":"2023-04-18","ids":{"openalex":"https://openalex.org/W4366238713","doi":"https://doi.org/10.1109/tnnls.2023.3265524","pmid":"https://pubmed.ncbi.nlm.nih.gov/37071516"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3265524","doi":"https://doi.org/10.1109/tnnls.2023.3265524","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3265524","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-b","cwts-core","dongbi-a","doyens","jufo-3","medline","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","pubmed"],"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/A5028293939","display_name":"Filippo Fedeli","orcid":"https://orcid.org/0000-0001-5991-2029","observed_orcids":["https://orcid.org/0000-0001-5991-2029"]},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Filippo Fedeli","raw_affiliation_strings":["Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy"],"raw_orcid":"https://orcid.org/0000-0001-5991-2029","affiliations":[{"raw_affiliation_string":"Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037963323","display_name":"Alberto Maria Metelli","orcid":"https://orcid.org/0000-0002-3424-5212","observed_orcids":["https://orcid.org/0000-0002-3424-5212"]},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alberto Maria Metelli","raw_affiliation_strings":["Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy"],"raw_orcid":"https://orcid.org/0000-0002-3424-5212","affiliations":[{"raw_affiliation_string":"Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039887680","display_name":"Francesco Trov\u00f2","orcid":"https://orcid.org/0000-0001-5796-7667","observed_orcids":["https://orcid.org/0000-0001-5796-7667"]},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Francesco Trov\u00f2","raw_affiliation_strings":["Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy"],"raw_orcid":"https://orcid.org/0000-0001-5796-7667","affiliations":[{"raw_affiliation_string":"Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy","institution_ids":["https://openalex.org/I93860229"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017130830","display_name":"Marcello Restelli","orcid":"https://orcid.org/0000-0002-6322-1076","observed_orcids":["https://orcid.org/0000-0002-6322-1076"]},"institutions":[{"id":"https://openalex.org/I93860229","display_name":"Politecnico di Milano","ror":"https://ror.org/01nffqt88","country_code":"IT","type":"education","lineage":["https://openalex.org/I93860229"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Marcello Restelli","raw_affiliation_strings":["Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy"],"raw_orcid":"https://orcid.org/0000-0002-6322-1076","affiliations":[{"raw_affiliation_string":"Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy","institution_ids":["https://openalex.org/I93860229"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I93860229"],"apc_list":{"value":2345,"currency":"USD","value_usd":2345},"apc_paid":null,"fwci":0.9256,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.74499977,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":"34","issue":"10","first_page":"6813","last_page":"6823"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":1.0,"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":1.0,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0,"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/T12676","display_name":"Machine Learning and ELM","score":0.0,"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/concept-drift","display_name":"concept drift","score":0.7609999775886536},{"id":"https://openalex.org/keywords/distribution-shift","display_name":"distribution shift","score":0.7360000014305115},{"id":"https://openalex.org/keywords/importance-weighting","display_name":"importance weighting","score":0.8880000114440918},{"id":"https://openalex.org/keywords/drift-detection","display_name":"drift detection","score":0.7400000095367432}],"concepts":[{"id":"https://openalex.org/C60777511","wikidata":"https://www.wikidata.org/wiki/Q3045002","display_name":"Concept drift","level":3,"score":0.908735990524292},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7646998167037964},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7561687231063843},{"id":"https://openalex.org/C2777611316","wikidata":"https://www.wikidata.org/wiki/Q39045282","display_name":"Streaming data","level":2,"score":0.6446927189826965},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.618116557598114},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.5929932594299316},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.5154374837875366},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5011630058288574},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48680540919303894},{"id":"https://openalex.org/C107321475","wikidata":"https://www.wikidata.org/wiki/Q5374254","display_name":"Empirical risk minimization","level":2,"score":0.46734410524368286},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.4535530209541321},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3410208225250244},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.2894901633262634},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14713987708091736},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1417948603630066},{"id":"https://openalex.org/C155202549","wikidata":"https://www.wikidata.org/wiki/Q178803","display_name":"International trade","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2023.3265524","doi":"https://doi.org/10.1109/tnnls.2023.3265524","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3265524","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-b","cwts-core","dongbi-a","doyens","jufo-3","medline","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37071516","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37071516","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":"Journal Article"},{"id":"pmh:oai:re.public.polimi.it:11311/1236403","doi":null,"is_oa":false,"landing_page_url":"https://hdl.handle.net/11311/1236403","pdf_url":null,"source":{"id":"https://openalex.org/S4306400312","display_name":"Virtual Community of Pathological Anatomy (University of Castilla La Mancha)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I79189158","host_organization_name":"University of Castilla-La Mancha","host_organization_lineage":["https://openalex.org/I79189158"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W91088564","https://openalex.org/W1483307070","https://openalex.org/W1525647652","https://openalex.org/W1529840045","https://openalex.org/W1585854823","https://openalex.org/W1985602045","https://openalex.org/W1999038366","https://openalex.org/W2000454347","https://openalex.org/W2014268383","https://openalex.org/W2016159616","https://openalex.org/W2022775778","https://openalex.org/W2034368206","https://openalex.org/W2040731319","https://openalex.org/W2051903196","https://openalex.org/W2052283750","https://openalex.org/W2068319486","https://openalex.org/W2072863821","https://openalex.org/W2073256825","https://openalex.org/W2074988520","https://openalex.org/W2086206379","https://openalex.org/W2090346540","https://openalex.org/W2097178527","https://openalex.org/W2099419573","https://openalex.org/W2111355007","https://openalex.org/W2113651538","https://openalex.org/W2133088989","https://openalex.org/W2134125037","https://openalex.org/W2134385409","https://openalex.org/W2143991132","https://openalex.org/W2158733996","https://openalex.org/W2160512933","https://openalex.org/W2167845177","https://openalex.org/W2170935389","https://openalex.org/W2289463038","https://openalex.org/W2325067522","https://openalex.org/W2520599539","https://openalex.org/W2552178666","https://openalex.org/W2591909298","https://openalex.org/W2602516395","https://openalex.org/W2619016545","https://openalex.org/W2741081039","https://openalex.org/W2768348081","https://openalex.org/W2890597452","https://openalex.org/W2896209868","https://openalex.org/W2902929648","https://openalex.org/W2945269249","https://openalex.org/W2963334956","https://openalex.org/W2982649420","https://openalex.org/W3003804390","https://openalex.org/W3013949960","https://openalex.org/W3082245592","https://openalex.org/W3159649695","https://openalex.org/W3199780937","https://openalex.org/W3212929567","https://openalex.org/W4231580960","https://openalex.org/W4235151464","https://openalex.org/W4248721357","https://openalex.org/W4286483098","https://openalex.org/W4293849739"],"related_works":["https://openalex.org/W7152997947","https://openalex.org/W7150121874","https://openalex.org/W7135417005","https://openalex.org/W2992362249","https://openalex.org/W4313158095","https://openalex.org/W2740428142","https://openalex.org/W3010959694","https://openalex.org/W3170299155","https://openalex.org/W4403091789","https://openalex.org/W4415234756"],"abstract_inverted_index":{"Distribution":[0],"drift":[1,60,66,80,102,147],"is":[2,81,103],"an":[3,50],"important":[4],"issue":[5],"for":[6,59,65,94,118],"practical":[7],"applications":[8],"of":[9,28,35,72,76,90],"machine":[10],"learning":[11,164],"(ML).":[12],"In":[13,41],"particular,":[14],"in":[15,49,144],"streaming":[16],"ML,":[17],"the":[18,26,33,70,77,86,95,106,120,126,145],"data":[19,97,175],"distribution":[20],"may":[21],"change":[22],"over":[23],"time,":[24],"yielding":[25],"problem":[27],"concept":[29],"drift,":[30],"which":[31],"affects":[32],"performance":[34],"learners":[36],"trained":[37],"with":[38,69],"outdated":[39],"data.":[40],"this":[42],"article,":[43],"we":[44,139,150],"focus":[45],"on":[46,170],"supervised":[47],"problems":[48],"online":[51],"nonstationary":[52],"setting,":[53],"introducing":[54],"a":[55,141],"novel":[56],"learner-agnostic":[57],"algorithm":[58],"adaptation,":[61],"namely":[62],"importance":[63,114],"weighting":[64],"adaptation":[67],"(IWDA),":[68],"goal":[71],"performing":[73],"efficient":[74],"retraining":[75],"learner":[78,107],"when":[79],"detected.":[82],"IWDA":[83,157],"incrementally":[84],"estimates":[85],"joint":[87],"probability":[88],"density":[89],"input":[91],"and":[92,159,173],"target":[93],"incoming":[96],"and,":[98],"as":[99,101],"soon":[100],"detected,":[104],"retrains":[105],"using":[108,130],"importance-weighted":[109],"empirical":[110],"risk":[111],"minimization.":[112],"The":[113],"weights":[115],"are":[116],"computed":[117],"all":[119,131],"samples":[121],"observed":[122],"so":[123],"far,":[124],"employing":[125],"estimated":[127],"densities,":[128],"thus,":[129],"available":[132],"information":[133],"efficiently.":[134],"After":[135],"presenting":[136],"our":[137],"approach,":[138],"provide":[140],"theoretical":[142],"analysis":[143],"abrupt":[146],"setting.":[148],"Finally,":[149],"present":[151],"numerical":[152],"simulations":[153],"that":[154],"illustrate":[155],"how":[156],"competes":[158],"often":[160],"outperforms":[161],"state-of-the-art":[162],"stream":[163],"techniques,":[165],"including":[166],"adaptive":[167],"ensemble":[168],"methods,":[169],"both":[171],"synthetic":[172],"real-world":[174],"benchmarks.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2023-04-20T00:00:00"}