{"id":"https://openalex.org/W4304481487","doi":"https://doi.org/10.1109/tnnls.2022.3208956","title":"Fast Multilabel Feature Selection via Global Relevance and Redundancy Optimization","display_name":"Fast Multilabel Feature Selection via Global Relevance and Redundancy Optimization","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4304481487","doi":"https://doi.org/10.1109/tnnls.2022.3208956","pmid":"https://pubmed.ncbi.nlm.nih.gov/36215379"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3208956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3208956","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/A5100706302","display_name":"Jia Zhang","orcid":"https://orcid.org/0000-0002-6079-2818"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jia Zhang","raw_affiliation_strings":["College of Information Science and Technology, Jinan University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-6079-2818","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041059015","display_name":"Yidong Lin","orcid":"https://orcid.org/0000-0001-7552-5555"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Zhangzhou Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yidong Lin","raw_affiliation_strings":["School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017961841","display_name":"Min Jiang","orcid":"https://orcid.org/0000-0003-2946-6974"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Min Jiang","raw_affiliation_strings":["Department of Artificial Intelligence, Fujian Key Laboratory of Machine Intelligence and Robotics, Xiamen University, Xiamen, China","Department of Artificial Intelligence and the Fujian Key Laboratory of Machine Intelligence and Robotics, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0003-2946-6974","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, Fujian Key Laboratory of Machine Intelligence and Robotics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]},{"raw_affiliation_string":"Department of Artificial Intelligence and the Fujian Key Laboratory of Machine Intelligence and Robotics, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081767617","display_name":"Shaozi Li","orcid":"https://orcid.org/0000-0001-5403-9945"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaozi Li","raw_affiliation_strings":["Department of Artificial Intelligence, Xiamen University, Xiamen, China"],"raw_orcid":"https://orcid.org/0000-0001-5403-9945","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120811349","display_name":"Yong Tang","orcid":"https://orcid.org/0000-0002-9812-0742"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Tang","raw_affiliation_strings":["School of Computer Science, South China Normal University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9812-0742","affiliations":[{"raw_affiliation_string":"School of Computer Science, South China Normal University, Guangzhou, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042542454","display_name":"Jinyi Long","orcid":"https://orcid.org/0000-0001-6150-987X"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinyi Long","raw_affiliation_strings":["College of Information Science and Technology, Jinan University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6150-987X","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082041657","display_name":"Jian Weng","orcid":null},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Weng","raw_affiliation_strings":["College of Information Science and Technology, Jinan University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-4067-8230","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025285243","display_name":"Kay Chen Tan","orcid":"https://orcid.org/0000-0002-6802-2463"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Kay Chen Tan","raw_affiliation_strings":["Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong","Department of Computing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-6802-2463","affiliations":[{"raw_affiliation_string":"Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Hong Kong","institution_ids":["https://openalex.org/I14243506"]},{"raw_affiliation_string":"Department of Computing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I14243506"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5100706302"],"corresponding_institution_ids":["https://openalex.org/I159948400"],"apc_list":null,"apc_paid":null,"fwci":5.4105,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.96228236,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"35","issue":"4","first_page":"5721","last_page":"5734"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9994999766349792,"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":0.9994999766349792,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9962999820709229,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9948999881744385,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6923578381538391},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.6621695160865784},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.5971032381057739},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5837016701698303},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5299611687660217},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5144439339637756},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49255141615867615},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.458992063999176},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4586084485054016},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.45281994342803955},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41742825508117676},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32033151388168335}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6923578381538391},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.6621695160865784},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.5971032381057739},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5837016701698303},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5299611687660217},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5144439339637756},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49255141615867615},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.458992063999176},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4586084485054016},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.45281994342803955},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41742825508117676},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32033151388168335},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3208956","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3208956","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:36215379","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36215379","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":[{"id":"https://openalex.org/G1002713634","display_name":null,"funder_award_id":"U1811263","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1536043703","display_name":null,"funder_award_id":"202201010498","funder_id":"https://openalex.org/F4320335480","funder_display_name":"Guangzhou Municipal Science and Technology Project"},{"id":"https://openalex.org/G2358695012","display_name":null,"funder_award_id":"2019A1515012175","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G2921174740","display_name":null,"funder_award_id":"2022A1515010468","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G5377523547","display_name":null,"funder_award_id":"62106084","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5803316663","display_name":null,"funder_award_id":"61773179","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6088860410","display_name":null,"funder_award_id":"2021B1515020076","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G6332536357","display_name":null,"funder_award_id":"21621026","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320335480","display_name":"Guangzhou Municipal Science and Technology Project","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W142187185","https://openalex.org/W146853821","https://openalex.org/W636917482","https://openalex.org/W1575192016","https://openalex.org/W1923967535","https://openalex.org/W1972401983","https://openalex.org/W1981491391","https://openalex.org/W1992419399","https://openalex.org/W2025335430","https://openalex.org/W2029517229","https://openalex.org/W2044170702","https://openalex.org/W2052684427","https://openalex.org/W2053463056","https://openalex.org/W2063249739","https://openalex.org/W2086465730","https://openalex.org/W2090630554","https://openalex.org/W2114315281","https://openalex.org/W2118561568","https://openalex.org/W2119466907","https://openalex.org/W2154053567","https://openalex.org/W2156935079","https://openalex.org/W2176228818","https://openalex.org/W2338318698","https://openalex.org/W2398606097","https://openalex.org/W2507677290","https://openalex.org/W2522701101","https://openalex.org/W2540382275","https://openalex.org/W2569112930","https://openalex.org/W2570565373","https://openalex.org/W2594029683","https://openalex.org/W2608997727","https://openalex.org/W2611743072","https://openalex.org/W2742683956","https://openalex.org/W2788125153","https://openalex.org/W2803748664","https://openalex.org/W2811296027","https://openalex.org/W2881233020","https://openalex.org/W2897768208","https://openalex.org/W2898240335","https://openalex.org/W2905927259","https://openalex.org/W2948768062","https://openalex.org/W2948831026","https://openalex.org/W2973358067","https://openalex.org/W2982208318","https://openalex.org/W2983276939","https://openalex.org/W2996966849","https://openalex.org/W2997546679","https://openalex.org/W2998727463","https://openalex.org/W3022782153","https://openalex.org/W3034775104","https://openalex.org/W3081164334","https://openalex.org/W3083230032","https://openalex.org/W3105524694","https://openalex.org/W3198831142","https://openalex.org/W4298982457","https://openalex.org/W6632714361","https://openalex.org/W6680361382","https://openalex.org/W6685974025","https://openalex.org/W6726030733","https://openalex.org/W6732103313","https://openalex.org/W6741642434"],"related_works":["https://openalex.org/W2085384747","https://openalex.org/W2088166309","https://openalex.org/W1891216533","https://openalex.org/W2106071040","https://openalex.org/W4312133475","https://openalex.org/W4238976562","https://openalex.org/W2276587472","https://openalex.org/W4248323080","https://openalex.org/W2156571267","https://openalex.org/W4308273529"],"abstract_inverted_index":{"Information":[0],"theoretical-based":[1],"methods":[2,25],"have":[3,193],"attracted":[4],"a":[5,27,56,68,90,117,208],"great":[6],"attention":[7],"in":[8,87,147,167],"recent":[9],"years":[10],"and":[11,37,74,102,135,157,173,223],"gained":[12],"promising":[13,155],"results":[14],"for":[15,92,197],"multilabel":[16,203],"feature":[17,95,103],"selection":[18],"(MLFS).":[19],"Nevertheless,":[20],"most":[21],"of":[22,34,45,169,177,202,225],"the":[23,31,43,80,125,143,149,175,183,199,212,221],"existing":[24],"consider":[26],"heuristic":[28],"way":[29],"to":[30,54,78,115,130,163,181,210],"grid":[32],"search":[33],"important":[35],"features,":[36,136,170],"they":[38,51],"may":[39],"also":[40],"suffer":[41],"from":[42],"issue":[44],"fully":[46],"utilizing":[47],"labeling":[48],"information.":[49],"Thus,":[50],"are":[52,105,152,161],"probable":[53],"deliver":[55],"suboptimal":[57],"result":[58,185],"with":[59,186,214],"heavy":[60],"computational":[61],"burden.":[62],"In":[63],"this":[64],"article,":[65],"we":[66,127,206],"propose":[67],"general":[69],"optimization":[70,76],"framework":[71,176],"global":[72,118],"relevance":[73,98],"redundancy":[75,104],"(GRRO)":[77],"solve":[79],"learning":[81],"problem.":[82],"The":[83],"main":[84],"technical":[85],"contribution":[86],"GRRO":[88,129,178],"is":[89,179],"formulation":[91,209],"MLFS":[93],"while":[94],"relevance,":[96],"label":[97,100],"(i.e.,":[99],"correlation),":[101],"taken":[106],"into":[107],"account,":[108],"which":[109,148],"can":[110],"avoid":[111],"repetitive":[112],"entropy":[113],"calculations":[114,166],"obtain":[116],"optimal":[119,184],"solution":[120],"efficiently.":[121],"To":[122],"further":[123],"improve":[124],"efficiency,":[126],"extend":[128],"filter":[131],"out":[132],"inessential":[133],"labels":[134,156,172],"thus":[137],"facilitating":[138],"fast":[139],"MLFS.":[140],"We":[141],"call":[142],"extension":[144],"as":[145],"GRROfast,":[146],"key":[150],"insights":[151],"twofold:":[153],"1)":[154],"related":[158],"relevant":[159],"features":[160],"investigated":[162],"reduce":[164],"ineffective":[165],"terms":[168],"even":[171],"2)":[174],"reconstructed":[180],"generate":[182],"an":[187,194],"ensemble.":[188],"Moreover,":[189],"our":[190,226],"proposed":[191,227],"algorithms":[192],"excellent":[195],"mechanism":[196],"exploiting":[198],"inherent":[200],"properties":[201],"data;":[204],"specifically,":[205],"provide":[207],"enhance":[211],"proposal":[213],"label-specific":[215],"features.":[216],"Extensive":[217],"experiments":[218],"clearly":[219],"reveal":[220],"effectiveness":[222],"efficiency":[224],"algorithms.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}