{"id":"https://openalex.org/W4281780077","doi":"https://doi.org/10.1145/3538708","title":"Generative Multi-Label Correlation Learning","display_name":"Generative Multi-Label Correlation Learning","publication_year":2022,"publication_date":"2022-06-06","ids":{"openalex":"https://openalex.org/W4281780077","doi":"https://doi.org/10.1145/3538708"},"language":"en","primary_location":{"id":"doi:10.1145/3538708","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3538708","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"type":"article","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/A5101444260","display_name":"Lichen Wang","orcid":"https://orcid.org/0000-0002-3741-9492"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lichen Wang","raw_affiliation_strings":["Northeastern University, Boston, Massachusetts"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, Massachusetts","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083458247","display_name":"Zhengming Ding","orcid":"https://orcid.org/0000-0002-6994-5278"},"institutions":[{"id":"https://openalex.org/I114832834","display_name":"Tulane University","ror":"https://ror.org/04vmvtb21","country_code":"US","type":"education","lineage":["https://openalex.org/I114832834"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhengming Ding","raw_affiliation_strings":["Tulane University, New Orleans, Louisiana"],"affiliations":[{"raw_affiliation_string":"Tulane University, New Orleans, Louisiana","institution_ids":["https://openalex.org/I114832834"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002104929","display_name":"Kasey Lee","orcid":"https://orcid.org/0000-0002-7956-1876"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kasey Lee","raw_affiliation_strings":["Northeastern University, Boston, Massachusetts"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, Massachusetts","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053165370","display_name":"Seungju Han","orcid":"https://orcid.org/0000-0001-7293-1419"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seungju Han","raw_affiliation_strings":["Samsung Electronics, Suwon-si, Gyeonggi-do, Korea"],"affiliations":[{"raw_affiliation_string":"Samsung Electronics, Suwon-si, Gyeonggi-do, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084450104","display_name":"Jae\u2010Joon Han","orcid":"https://orcid.org/0000-0002-6505-6529"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jae-Joon Han","raw_affiliation_strings":["Samsung Electronics, Suwon-si, Gyeonggi-do, Korea"],"affiliations":[{"raw_affiliation_string":"Samsung Electronics, Suwon-si, Gyeonggi-do, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045861786","display_name":"Changkyu Choi","orcid":"https://orcid.org/0000-0002-1470-8662"},"institutions":[{"id":"https://openalex.org/I2250650973","display_name":"Samsung (South Korea)","ror":"https://ror.org/04w3jy968","country_code":"KR","type":"company","lineage":["https://openalex.org/I2250650973"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Changkyu Choi","raw_affiliation_strings":["Samsung Electronics, Suwon-si, Gyeonggi-do, Korea"],"affiliations":[{"raw_affiliation_string":"Samsung Electronics, Suwon-si, Gyeonggi-do, Korea","institution_ids":["https://openalex.org/I2250650973"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005819096","display_name":"Yun Fu","orcid":"https://orcid.org/0000-0002-5098-2853"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yun Fu","raw_affiliation_strings":["Northeastern University, Boston, Massachusetts"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, Massachusetts","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101444260"],"corresponding_institution_ids":["https://openalex.org/I12912129"],"apc_list":null,"apc_paid":null,"fwci":0.3977,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.65742321,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"17","issue":"2","first_page":"1","last_page":"19"},"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/T11309","display_name":"Music and Audio Processing","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9779000282287598,"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":0.7317689657211304},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.642211377620697},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6303907632827759},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5899643898010254},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.581538200378418},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4605262875556946},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.43509641289711},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3926179111003876},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.341374933719635},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14435544610023499}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7317689657211304},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.642211377620697},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6303907632827759},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5899643898010254},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.581538200378418},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4605262875556946},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.43509641289711},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3926179111003876},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.341374933719635},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14435544610023499},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3538708","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3538708","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1797268635","https://openalex.org/W1875842236","https://openalex.org/W1998839399","https://openalex.org/W2027869746","https://openalex.org/W2070148066","https://openalex.org/W2126523478","https://openalex.org/W2128532956","https://openalex.org/W2133510502","https://openalex.org/W2133665775","https://openalex.org/W2141282920","https://openalex.org/W2143854982","https://openalex.org/W2156935079","https://openalex.org/W2165698076","https://openalex.org/W2198007625","https://openalex.org/W2536305071","https://openalex.org/W2584571478","https://openalex.org/W2611632661","https://openalex.org/W2736688973","https://openalex.org/W2808022112","https://openalex.org/W2808417254","https://openalex.org/W2884886306","https://openalex.org/W2962793481","https://openalex.org/W2963052338","https://openalex.org/W2963162313","https://openalex.org/W2963697527","https://openalex.org/W2964181345","https://openalex.org/W2991327923","https://openalex.org/W3003930651","https://openalex.org/W3037422790","https://openalex.org/W3095707208","https://openalex.org/W3117196003","https://openalex.org/W3156044630","https://openalex.org/W3171998492","https://openalex.org/W3177232285","https://openalex.org/W3185442830","https://openalex.org/W3197393979"],"related_works":["https://openalex.org/W2380075625","https://openalex.org/W4237784285","https://openalex.org/W4390549206","https://openalex.org/W3137171911","https://openalex.org/W4248905757","https://openalex.org/W2374712251","https://openalex.org/W4383031710","https://openalex.org/W2386000789","https://openalex.org/W4281776617","https://openalex.org/W4385572443"],"abstract_inverted_index":{"In":[0,43,128],"real-world":[1],"applications,":[2],"a":[3,25,96,116,130],"single":[4],"instance":[5],"could":[6,52],"have":[7],"more":[8,26,57,153],"than":[9],"one":[10],"label.":[11],"To":[12,90],"solve":[13],"this":[14],"task,":[15],"multi-label":[16,131],"learning":[17,50],"methods":[18],"emerged":[19],"in":[20,158],"recent":[21],"years.":[22],"It":[23,143],"is":[24,134],"challenging":[27],"problem":[28],"for":[29],"many":[30],"reasons,":[31],"such":[32],"as":[33,87],"complex":[34],"label":[35,38,62,80,112,117,140],"correlation,":[36],"long-tail":[37,139],"distribution,":[39],"and":[40,48,60,69,78,98,107,124,151,169],"data":[41],"shortage.":[42],"general,":[44],"overcoming":[45],"these":[46,65,92],"challenges":[47],"bettering":[49],"performance":[51],"be":[53],"achieved":[54],"by":[55,114],"utilizing":[56],"training":[58],"samples":[59,150],"including":[61],"correlations.":[63],"However,":[64],"solutions":[66],"are":[67,74,161],"expensive":[68],"inflexible.":[70],"Large-scale,":[71],"well-labeled":[72],"datasets":[73],"difficult":[75],"to":[76,136],"obtain,":[77],"building":[79],"correlation":[81,118],"maps":[82],"requires":[83],"task-specific":[84],"semantic":[85],"information":[86],"prior":[88],"knowledge.":[89],"address":[91],"limitations,":[93],"we":[94],"propose":[95],"general":[97],"compact":[99],"Multi-Label":[100],"Correlation":[101],"Learning":[102],"(MUCO)":[103],"framework.":[104],"MUCO":[105],"explicitly":[106],"effectively":[108],"learns":[109],"the":[110,138,145,167,177,181],"latent":[111],"correlations":[113],"updating":[115],"tensor,":[119],"which":[120],"provides":[121],"highly":[122],"accurate":[123],"interpretable":[125],"prediction":[126],"results.":[127],"addition,":[129],"generative":[132],"strategy":[133],"deployed":[135],"handle":[137],"distribution":[141],"challenge.":[142],"borrows":[144],"visual":[146],"clues":[147],"from":[148],"limited":[149],"synthesizes":[152],"diverse":[154],"samples.":[155],"All":[156],"networks":[157],"our":[159],"model":[160],"optimized":[162],"simultaneously.":[163],"Extensive":[164],"experiments":[165],"illustrate":[166],"effectiveness":[168,178],"efficiency":[170],"of":[171,179],"MUCO.":[172],"Ablation":[173],"studies":[174],"further":[175],"prove":[176],"all":[180],"modules.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}