{"id":"https://openalex.org/W4386596855","doi":"https://doi.org/10.1109/icip49359.2023.10222329","title":"Cost-Efficient Multi-Instance Multi-Label Active Learning Via Correlation of Features","display_name":"Cost-Efficient Multi-Instance Multi-Label Active Learning Via Correlation of Features","publication_year":2023,"publication_date":"2023-09-11","ids":{"openalex":"https://openalex.org/W4386596855","doi":"https://doi.org/10.1109/icip49359.2023.10222329"},"language":"en","primary_location":{"id":"doi:10.1109/icip49359.2023.10222329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip49359.2023.10222329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Image Processing (ICIP)","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/A5108862737","display_name":"Guoliang Su","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoliang Su","raw_affiliation_strings":["Southwest University,College of Computer and Information Science","College of Computer and Information Science, Southwest University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University,College of Computer and Information Science","institution_ids":["https://openalex.org/I142108993"]},{"raw_affiliation_string":"College of Computer and Information Science, Southwest University","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104167334","display_name":"Zhangquan Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhangquan Wu","raw_affiliation_strings":["Southwest University,College of Computer and Information Science","College of Computer and Information Science, Southwest University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University,College of Computer and Information Science","institution_ids":["https://openalex.org/I142108993"]},{"raw_affiliation_string":"College of Computer and Information Science, Southwest University","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109652768","display_name":"Yujia Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yujia Ye","raw_affiliation_strings":["Southwest University,College of Computer and Information Science","College of Computer and Information Science, Southwest University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University,College of Computer and Information Science","institution_ids":["https://openalex.org/I142108993"]},{"raw_affiliation_string":"College of Computer and Information Science, Southwest University","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102019541","display_name":"M. Chen","orcid":"https://orcid.org/0000-0002-2386-7649"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maoxing Chen","raw_affiliation_strings":["Thundersoft (Chongqing) Automotive Technology Co., Ltd"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Thundersoft (Chongqing) Automotive Technology Co., Ltd","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063215334","display_name":"Jun Zhou","orcid":"https://orcid.org/0000-0003-4353-1621"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhou","raw_affiliation_strings":["Southwest University,College of Computer and Information Science","College of Computer and Information Science, Southwest University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Southwest University,College of Computer and Information Science","institution_ids":["https://openalex.org/I142108993"]},{"raw_affiliation_string":"College of Computer and Information Science, Southwest University","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"410","last_page":"414"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9987999796867371,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9987999796867371,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9976999759674072,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9801999926567078,"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/computer-science","display_name":"Computer science","score":0.8115755319595337},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.717264711856842},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.6063841581344604},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5925611257553101},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.577446460723877},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5604481101036072},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5320751667022705},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4753287136554718},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38722068071365356},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08678150177001953}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8115755319595337},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.717264711856842},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.6063841581344604},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5925611257553101},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.577446460723877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5604481101036072},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5320751667022705},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4753287136554718},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38722068071365356},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08678150177001953},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip49359.2023.10222329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip49359.2023.10222329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3196577821","display_name":null,"funder_award_id":"22274134","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1971400763","https://openalex.org/W2027266161","https://openalex.org/W2029517229","https://openalex.org/W2044200706","https://openalex.org/W2114315281","https://openalex.org/W2137917285","https://openalex.org/W2165484066","https://openalex.org/W2200666166","https://openalex.org/W2609724507","https://openalex.org/W2740505281","https://openalex.org/W2748525783","https://openalex.org/W2885073348","https://openalex.org/W2903158431","https://openalex.org/W2907192597","https://openalex.org/W2935162632","https://openalex.org/W2964154753","https://openalex.org/W2988426147","https://openalex.org/W3042816745","https://openalex.org/W3109636347","https://openalex.org/W3127152040","https://openalex.org/W3188862374","https://openalex.org/W3193305990","https://openalex.org/W6653695713","https://openalex.org/W6713235370"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W4281776617"],"abstract_inverted_index":{"Multi-instance":[0],"multi-label":[1,119],"active":[2],"learning":[3],"(MIMAL)":[4],"usually":[5],"uses":[6],"example":[7,34,80],"uncertainty":[8],"and":[9,56,91,134],"label":[10],"correlation":[11,32,88],"to":[12,58,81],"select":[13],"the":[14,20,24,31,52,68,73,79,82,87,94,104,111,126],"most":[15,105],"valuable":[16],"example-label":[17,38,98,113],"pairs,":[18],"maximizing":[19],"learner\u2019s":[21],"performance.":[22],"However,":[23],"existing":[25],"MIMAL":[26,46,128,140],"solutions":[27],"do":[28],"not":[29],"consider":[30],"of":[33,75],"features":[35,57,77,90],"when":[36],"selecting":[37,97],"pairs.":[39,99,114],"Here,":[40],"this":[41],"paper":[42],"proposes":[43],"a":[44],"novel":[45],"framework":[47],"that":[48,125],"can":[49,129],"effectively":[50,71],"exploit":[51],"relationship":[53],"between":[54,89],"examples":[55,92],"reduce":[59],"annotation":[60],"cost.":[61],"We":[62],"first":[63],"perform":[64],"feature":[65],"screening":[66],"on":[67,78,118],"examples.":[69],"It":[70],"eliminates":[72],"interference":[74],"useless":[76],"annotations.":[83],"Next,":[84],"we":[85,101],"quantify":[86],"as":[93],"basis":[95],"for":[96,103],"Finally,":[100],"query":[102,132],"likely":[106],"positive":[107],"subexample-label":[108],"pair":[109],"among":[110],"selected":[112],"The":[115],"extensive":[116],"experiments":[117],"datasets":[120],"from":[121],"diverse":[122],"domains":[123],"show":[124],"proposed":[127],"better":[130],"save":[131],"cost":[133],"achieve":[135],"superior":[136],"performance":[137],"than":[138],"state-of-the-art":[139],"methods.":[141]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}