{"id":"https://openalex.org/W3201612537","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533304","title":"Joint Distribution Adaptation via Wasserstein Adversarial Training","display_name":"Joint Distribution Adaptation via Wasserstein Adversarial Training","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3201612537","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533304","mag":"3201612537"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533304","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533304","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","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/A5100444086","display_name":"Xiaolu Wang","orcid":"https://orcid.org/0000-0001-9806-8369"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiaolu Wang","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061410855","display_name":"Wenyong Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wenyong Zhang","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100624454","display_name":"Xin Shen","orcid":"https://orcid.org/0009-0006-2699-3292"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xin Shen","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020742575","display_name":"Huikang Liu","orcid":"https://orcid.org/0000-0002-8952-3339"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Huikang Liu","raw_affiliation_strings":["Imperial College Business School, Imperial College London, London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College Business School, Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12334432,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"137","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994000196456909,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994000196456909,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9491000175476074,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9222999811172485,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6887481212615967},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.674634575843811},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6489648818969727},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5953370332717896},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5568768978118896},{"id":"https://openalex.org/keywords/minimax","display_name":"Minimax","score":0.5438228249549866},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.535599946975708},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5034708380699158},{"id":"https://openalex.org/keywords/joint-probability-distribution","display_name":"Joint probability distribution","score":0.4962654709815979},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46186429262161255},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4535773694515228},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.4446631968021393},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4198405146598816},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4181826412677765},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35814785957336426},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.24924930930137634},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24231627583503723},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07866877317428589}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6887481212615967},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.674634575843811},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6489648818969727},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5953370332717896},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5568768978118896},{"id":"https://openalex.org/C149728462","wikidata":"https://www.wikidata.org/wiki/Q751319","display_name":"Minimax","level":2,"score":0.5438228249549866},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.535599946975708},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5034708380699158},{"id":"https://openalex.org/C18653775","wikidata":"https://www.wikidata.org/wiki/Q1333358","display_name":"Joint probability distribution","level":2,"score":0.4962654709815979},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46186429262161255},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4535773694515228},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.4446631968021393},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4198405146598816},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4181826412677765},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35814785957336426},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.24924930930137634},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24231627583503723},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07866877317428589},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533304","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533304","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W385466589","https://openalex.org/W1522301498","https://openalex.org/W1576445103","https://openalex.org/W1594039573","https://openalex.org/W1722318740","https://openalex.org/W1731081199","https://openalex.org/W1990989681","https://openalex.org/W2059979378","https://openalex.org/W2096873754","https://openalex.org/W2096943734","https://openalex.org/W2099471712","https://openalex.org/W2100659887","https://openalex.org/W2110158442","https://openalex.org/W2112796928","https://openalex.org/W2115403315","https://openalex.org/W2131953535","https://openalex.org/W2149466042","https://openalex.org/W2155541015","https://openalex.org/W2159291411","https://openalex.org/W2163302275","https://openalex.org/W2163605009","https://openalex.org/W2187089797","https://openalex.org/W2232010405","https://openalex.org/W2593768305","https://openalex.org/W2616287544","https://openalex.org/W2739748921","https://openalex.org/W2770645414","https://openalex.org/W2962879692","https://openalex.org/W2962997028","https://openalex.org/W2963187488","https://openalex.org/W2963777311","https://openalex.org/W2964121744","https://openalex.org/W2964278684","https://openalex.org/W2964288524","https://openalex.org/W3002944878","https://openalex.org/W3039256091","https://openalex.org/W3216759837","https://openalex.org/W4206471589","https://openalex.org/W4294375521","https://openalex.org/W4295521014","https://openalex.org/W4320013936","https://openalex.org/W6631190155","https://openalex.org/W6637542466","https://openalex.org/W6637618735","https://openalex.org/W6681637710","https://openalex.org/W6682778277","https://openalex.org/W6683633756","https://openalex.org/W6684149856","https://openalex.org/W6684191040","https://openalex.org/W6689534940","https://openalex.org/W6713955831","https://openalex.org/W6720111944","https://openalex.org/W6734871034","https://openalex.org/W6735913928","https://openalex.org/W6737976933","https://openalex.org/W6741832134","https://openalex.org/W6746789195","https://openalex.org/W6773224681"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W4246396837","https://openalex.org/W2482350142","https://openalex.org/W3176240006","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4288019534","https://openalex.org/W2147093486"],"abstract_inverted_index":{"This":[0],"paper":[1],"considers":[2],"the":[3,19,25,29,37,48,52,65,69,73,77,105,109,113,124,128,134,138,166,173],"unsupervised":[4],"domain":[5,38,79,94,140,168,216],"adaptation":[6,39,217],"problem,":[7],"in":[8,28,76,112,148],"which":[9,96],"we":[10,87,122],"want":[11],"to":[12,36,42,63,103,171,209],"find":[13],"a":[14,44,89,149,156],"good":[15],"prediction":[16,135],"function":[17],"on":[18,137,165,186,193],"unlabeled":[20],"target":[21,55,131,167],"domain,":[22],"by":[23],"utilizing":[24],"information":[26,75],"provided":[27,170],"labeled":[30],"source":[31,53,78,129,139],"domain.":[32],"A":[33,162],"common":[34],"approach":[35,92,146],"problem":[40],"is":[41,57,80,97,141,169,207],"learn":[43],"representation":[45,90,115,176],"space":[46,116],"where":[47],"distributional":[49],"discrepancy":[50],"of":[51,68,108,175],"and":[54,130,188,196],"domains":[56],"small.":[58],"Existing":[59],"methods":[60],"generally":[61],"tend":[62],"match":[64],"marginal":[66],"distributions":[67,107],"two":[70],"domains,":[71,132],"while":[72,133],"label":[74],"not":[81],"fully":[82],"exploited.":[83],"In":[84,120],"this":[85],"paper,":[86],"propose":[88],"learning":[91,177],"for":[93,117,178],"adaptation,":[95],"addressed":[98],"as":[99],"JODAWAT.":[100],"We":[101,182],"aim":[102],"adapt":[104],"joint":[106,179],"feature-label":[110],"pairs":[111],"shared":[114],"both":[118],"domains.":[119],"particular,":[121],"minimize":[123],"Wasserstein":[125],"distance":[126],"between":[127],"performance":[136,212],"also":[142],"guaranteed.":[143],"The":[144,199],"proposed":[145,205],"results":[147,201],"minimax":[150],"adversarial":[151],"training":[152],"procedure":[153],"that":[154,203],"incorporates":[155],"novel":[157],"split":[158],"gradient":[159],"penalty":[160],"term.":[161],"generalization":[163],"bound":[164],"reveal":[172],"efficacy":[174],"distribution":[180],"adaptation.":[181],"conduct":[183],"extensive":[184],"evaluations":[185],"JODAWAT,":[187],"test":[189],"its":[190],"classification":[191],"accuracy":[192],"multiple":[194],"synthetic":[195],"real":[197],"datasets.":[198],"experimental":[200],"justify":[202],"our":[204],"method":[206],"able":[208],"achieve":[210],"superior":[211],"compared":[213],"with":[214],"various":[215],"methods.":[218]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
