{"id":"https://openalex.org/W2963199592","doi":"https://doi.org/10.1109/tnnls.2018.2868649","title":"Pool-Based Sequential Active Learning for Regression","display_name":"Pool-Based Sequential Active Learning for Regression","publication_year":2018,"publication_date":"2018-09-27","ids":{"openalex":"https://openalex.org/W2963199592","doi":"https://doi.org/10.1109/tnnls.2018.2868649","mag":"2963199592","pmid":"https://pubmed.ncbi.nlm.nih.gov/30281482"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2018.2868649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2018.2868649","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,"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"},"type":"article","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/A5008740867","display_name":"Dongrui Wu","orcid":"https://orcid.org/0000-0002-7153-9703"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Dongrui Wu","raw_affiliation_strings":["DataNova LLC, Clifton Park, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-7153-9703","affiliations":[{"raw_affiliation_string":"DataNova LLC, Clifton Park, NY, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5008740867"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.3967,"has_fulltext":false,"cited_by_count":155,"citation_normalized_percentile":{"value":0.98040717,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"30","issue":"5","first_page":"1348","last_page":"1359"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","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/T12072","display_name":"Machine Learning and Algorithms","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/T12535","display_name":"Machine Learning and Data Classification","score":0.9983999729156494,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9857000112533569,"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/representativeness-heuristic","display_name":"Representativeness heuristic","score":0.9417548179626465},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.7572857141494751},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7271830439567566},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.6091583967208862},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6080271005630493},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5838661789894104},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.5596999526023865},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.4433537721633911},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.44314029812812805},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3370988965034485},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10544067621231079},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10305759310722351}],"concepts":[{"id":"https://openalex.org/C37381756","wikidata":"https://www.wikidata.org/wiki/Q20203288","display_name":"Representativeness heuristic","level":2,"score":0.9417548179626465},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7572857141494751},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7271830439567566},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6091583967208862},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6080271005630493},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5838661789894104},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.5596999526023865},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.4433537721633911},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.44314029812812805},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3370988965034485},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10544067621231079},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10305759310722351},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"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/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2018.2868649","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2018.2868649","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,"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:30281482","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30281482","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,"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":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W622321019","https://openalex.org/W652662681","https://openalex.org/W1528361845","https://openalex.org/W1568139284","https://openalex.org/W1573810412","https://openalex.org/W1599956645","https://openalex.org/W1825061555","https://openalex.org/W1977556410","https://openalex.org/W1978633512","https://openalex.org/W1985327665","https://openalex.org/W1993615002","https://openalex.org/W1998739300","https://openalex.org/W2002055708","https://openalex.org/W2014538668","https://openalex.org/W2018770010","https://openalex.org/W2026386069","https://openalex.org/W2061554433","https://openalex.org/W2080021732","https://openalex.org/W2097732741","https://openalex.org/W2110065044","https://openalex.org/W2110910681","https://openalex.org/W2114338449","https://openalex.org/W2115305054","https://openalex.org/W2128073546","https://openalex.org/W2128678390","https://openalex.org/W2131202893","https://openalex.org/W2142275721","https://openalex.org/W2144452292","https://openalex.org/W2149628368","https://openalex.org/W2160828669","https://openalex.org/W2170347328","https://openalex.org/W2171671120","https://openalex.org/W2177405552","https://openalex.org/W2295710691","https://openalex.org/W2341531400","https://openalex.org/W2903158431","https://openalex.org/W2949071206","https://openalex.org/W2963340415","https://openalex.org/W2964117520","https://openalex.org/W4230277160","https://openalex.org/W6636044972","https://openalex.org/W6655195918","https://openalex.org/W6677284661","https://openalex.org/W6679154154","https://openalex.org/W6679227803","https://openalex.org/W6683391390","https://openalex.org/W6756615331"],"related_works":["https://openalex.org/W3159631231","https://openalex.org/W4404624381","https://openalex.org/W4306248409","https://openalex.org/W4211213551","https://openalex.org/W2332151799","https://openalex.org/W2062728131","https://openalex.org/W1824075546","https://openalex.org/W2103926897","https://openalex.org/W2101250918","https://openalex.org/W3013165237"],"abstract_inverted_index":{"Active":[0],"learning":[1],"(AL)":[2],"is":[3],"a":[4,14,31,86],"machine-learning":[5],"approach":[6,61,89,110],"for":[7,49],"reducing":[8],"the":[9,23,38,66,96,99,103,121,126,152],"data":[10,146],"labeling":[11],"effort.":[12],"Given":[13],"pool":[15],"of":[16,133,142,154],"unlabeled":[17,69],"samples,":[18],"it":[19],"tries":[20],"to":[21,27,123],"select":[22],"most":[24,67],"useful":[25,68],"ones":[26],"label":[28],"so":[29],"that":[30,58],"model":[32],"built":[33],"from":[34,148],"them":[35],"can":[36,111],"achieve":[37],"best":[39],"possible":[40],"performance.":[41,127],"This":[42],"paper":[43],"focuses":[44],"on":[45,130],"pool-based":[46],"sequential":[47],"AL":[48],"regression":[50],"(ALR).":[51],"We":[52,83],"first":[53],"propose":[54,85],"three":[55],"essential":[56],"criteria":[57],"an":[59],"ALR":[60,79,88,118,157],"should":[62],"consider":[63],"in":[64,101,120],"selecting":[65],"samples:":[70],"informativeness,":[71],"representativeness,":[72],"and":[73,75,98,105,140],"diversity,":[74],"compare":[76],"four":[77],"existing":[78,117],"approaches":[80,119],"against":[81],"them.":[82],"then":[84],"new":[87],"using":[90],"passive":[91],"sampling,":[92],"which":[93],"considers":[94],"both":[95,102],"representativeness":[97],"diversity":[100],"initialization":[104],"subsequent":[106],"iterations.":[107],"Remarkably,":[108],"this":[109],"also":[112],"be":[113],"integrated":[114],"with":[115],"other":[116],"literature":[122],"further":[124],"improve":[125],"Extensive":[128],"experiments":[129],"11":[131],"University":[132,138,141],"California,":[134],"Irvine,":[135],"Carnegie":[136],"Mellon":[137],"StatLib,":[139],"Florida":[143],"Media":[144],"Core":[145],"sets":[147],"various":[149],"domains":[150],"verified":[151],"effectiveness":[153],"our":[155],"proposed":[156],"approaches.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":26},{"year":2022,"cited_by_count":24},{"year":2021,"cited_by_count":20},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":3}],"updated_date":"2026-07-25T15:57:00.446498","created_date":"2025-10-10T00:00:00"}
