{"id":"https://openalex.org/W4306926067","doi":"https://doi.org/10.1007/s10994-022-06236-2","title":"Towards adaptive unknown authentication for universal domain adaptation by classifier paradox","display_name":"Towards adaptive unknown authentication for universal domain adaptation by classifier paradox","publication_year":2022,"publication_date":"2022-10-20","ids":{"openalex":"https://openalex.org/W4306926067","doi":"https://doi.org/10.1007/s10994-022-06236-2"},"language":"en","primary_location":{"id":"doi:10.1007/s10994-022-06236-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-022-06236-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-022-06236-2.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10994-022-06236-2.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100714799","display_name":"Yunyun Wang","orcid":"https://orcid.org/0000-0002-5884-9408"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunyun Wang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing, 210046, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing, 210046, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100463098","display_name":"Yao Liu","orcid":"https://orcid.org/0000-0003-3382-798X"},"institutions":[{"id":"https://openalex.org/I41198531","display_name":"Nanjing University of Posts and Telecommunications","ror":"https://ror.org/043bpky34","country_code":"CN","type":"education","lineage":["https://openalex.org/I41198531"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Liu","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing, 210046, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Posts and Telecommunications, Nanjing, 210046, China","institution_ids":["https://openalex.org/I41198531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101596072","display_name":"Songcan Chen","orcid":"https://orcid.org/0000-0002-5164-0070"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Songcan Chen","raw_affiliation_strings":["School of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 210023, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 210023, China","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101596072"],"corresponding_institution_ids":["https://openalex.org/I9842412"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.1388,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55695107,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"113","issue":"4","first_page":"1623","last_page":"1641"},"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":0.9995999932289124,"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":0.9995999932289124,"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/classifier","display_name":"Classifier (UML)","score":0.790068507194519},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6998244524002075},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6490611433982849},{"id":"https://openalex.org/keywords/decision-boundary","display_name":"Decision boundary","score":0.6155325770378113},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.54032963514328},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5121638774871826},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.46815088391304016},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4661617875099182},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4641965627670288},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4416669011116028},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4216015934944153},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4199589788913727},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36951905488967896},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24908673763275146},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.10640779137611389}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.790068507194519},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6998244524002075},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6490611433982849},{"id":"https://openalex.org/C42023084","wikidata":"https://www.wikidata.org/wiki/Q5249231","display_name":"Decision boundary","level":3,"score":0.6155325770378113},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.54032963514328},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5121638774871826},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.46815088391304016},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4661617875099182},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4641965627670288},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4416669011116028},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4216015934944153},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4199589788913727},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36951905488967896},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24908673763275146},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.10640779137611389},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10994-022-06236-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-022-06236-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-022-06236-2.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10994-022-06236-2","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-022-06236-2","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-022-06236-2.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1990521796","display_name":null,"funder_award_id":"62176118","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G37568934","display_name":null,"funder_award_id":"Grant","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6535958650","display_name":null,"funder_award_id":"62076124","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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4306926067.pdf","grobid_xml":"https://content.openalex.org/works/W4306926067.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1722318740","https://openalex.org/W2104094955","https://openalex.org/W2117539524","https://openalex.org/W2131715540","https://openalex.org/W2159291411","https://openalex.org/W2194775991","https://openalex.org/W2627183927","https://openalex.org/W2779610669","https://openalex.org/W2798593490","https://openalex.org/W2885722640","https://openalex.org/W2904373341","https://openalex.org/W2948069880","https://openalex.org/W2948429981","https://openalex.org/W2962687275","https://openalex.org/W2964288524","https://openalex.org/W2981720610","https://openalex.org/W2986381065","https://openalex.org/W2990138404","https://openalex.org/W3009033475","https://openalex.org/W3034454087","https://openalex.org/W3097526063","https://openalex.org/W3102842772","https://openalex.org/W3175269419","https://openalex.org/W3177151237","https://openalex.org/W3177391608","https://openalex.org/W3199097846","https://openalex.org/W4214671648","https://openalex.org/W6637618735","https://openalex.org/W6713955831","https://openalex.org/W6725448924","https://openalex.org/W6756040250"],"related_works":["https://openalex.org/W2900140651","https://openalex.org/W2408513648","https://openalex.org/W2914037311","https://openalex.org/W2912497862","https://openalex.org/W2886321183","https://openalex.org/W2150210531","https://openalex.org/W1545578054","https://openalex.org/W4282039363","https://openalex.org/W2118518475","https://openalex.org/W2294615021"],"abstract_inverted_index":{"Universal":[0],"domain":[1,8,14,182],"adaptation":[2,9],"(UniDA)":[3],"is":[4,61,128,184],"a":[5,45,66,78,95,125,138,152],"general":[6],"unsupervised":[7],"setting,":[10],"which":[11,71],"addresses":[12],"both":[13,208],"and":[15,50,69,77,210],"label":[16],"shifts":[17],"in":[18,24,30,87,186],"adaptation.":[19],"Its":[20],"main":[21],"challenge":[22],"lies":[23],"how":[25],"to":[26,39,64,74,117,144],"identify":[27],"target":[28],"samples":[29,109,143,191],"unshared":[31],"or":[32,167],"unknown":[33],"classes.":[34,89,122],"Previous":[35],"methods":[36],"commonly":[37],"strive":[38],"depict":[40],"sample":[41],"\u201cconfidence\u201d":[42,67],"along":[43],"with":[44,99,110,131,164,200],"threshold":[46,70],"for":[47,178],"rejecting":[48],"unknowns,":[49],"align":[51],"feature":[52,176,201],"distributions":[53],"of":[54,80,85,119,134,146,175],"shared":[55,88,179],"classes":[56],"across":[57,192],"domains.":[58],"However,":[59],"it":[60],"still":[62],"hard":[63],"pre-specify":[65],"criterion":[68],"are":[72,113,169],"adaptive":[73,100],"different":[75],"tasks,":[76],"mis-prediction":[79],"unknowns":[81,115],"further":[82,156],"incurs":[83],"mis-alignment":[84],"features":[86],"In":[90,123],"this":[91],"paper,":[92],"we":[93],"propose":[94],"new":[96],"UniDA":[97],"method":[98],"Unknown":[101],"Authentication":[102],"by":[103,160],"Classifier":[104],"Paradox":[105],"(UACP),":[106],"considering":[107],"that":[108,190],"paradoxical":[111],"predictions":[112],"probably":[114],"belonging":[116],"none":[118],"the":[120,147,158,195],"source":[121,149],"UACP,":[124],"composite":[126],"classifier":[127],"jointly":[129],"designed":[130],"two":[132],"types":[133],"predictors.":[135],"That":[136],"is,":[137],"multi-class":[139],"(MC)":[140],"predictor":[141,155],"classifies":[142],"one":[145],"multiple":[148],"classes,":[150,180],"while":[151],"binary":[153],"one-vs-all":[154],"verifies":[157],"prediction":[159],"MC":[161],"predictor.":[162],"Samples":[163],"verification":[165],"failure":[166],"paradox":[168],"identified":[170],"as":[171],"unknowns.":[172],"Further,":[173],"instead":[174],"alignment":[177,183],"implicit":[181],"conducted":[185],"output":[187],"space":[188],"such":[189],"domains":[193],"share":[194],"same":[196],"decision":[197],"boundary,":[198],"though":[199],"discrepancy.":[202],"Empirical":[203],"results":[204],"validate":[205],"UACP":[206],"under":[207],"open-set":[209],"universal":[211],"UDA":[212],"settings.":[213]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}
