{"id":"https://openalex.org/W3015094643","doi":"https://doi.org/10.3233/ida-194516","title":"Biased transfer matching for less overlapping degree for unsupervised domain adaptation","display_name":"Biased transfer matching for less overlapping degree for unsupervised domain adaptation","publication_year":2020,"publication_date":"2020-03-27","ids":{"openalex":"https://openalex.org/W3015094643","doi":"https://doi.org/10.3233/ida-194516","mag":"3015094643"},"language":"en","primary_location":{"id":"doi:10.3233/ida-194516","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-194516","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","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/A5025503767","display_name":"Yiran Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yiran Wen","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101124826","display_name":"Xiu Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiu Cao","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100683379","display_name":"Xue-ping Wang","orcid":"https://orcid.org/0000-0003-4376-9859"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueping Wang","raw_affiliation_strings":["School of Computer Science, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035481964","display_name":"Fangyuan Liu","orcid":"https://orcid.org/0000-0003-2606-753X"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangyuan Liu","raw_affiliation_strings":["School of Electronic, Wuhan University, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic, Wuhan University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5025503767"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.134,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56256972,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"24","issue":"2","first_page":"409","last_page":"425"},"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":0.9997000098228455,"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":0.9997000098228455,"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/T12676","display_name":"Machine Learning and ELM","score":0.9771999716758728,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9693999886512756,"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":0.6856288313865662},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.647913932800293},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6005151271820068},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5540326833724976},{"id":"https://openalex.org/keywords/degree","display_name":"Degree (music)","score":0.5408191680908203},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5228222608566284},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.49811244010925293},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.4690589904785156},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4369143843650818},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4270067811012268},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3812521994113922},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37071293592453003},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34787216782569885},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2631590962409973},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.25122570991516113}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6856288313865662},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.647913932800293},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6005151271820068},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5540326833724976},{"id":"https://openalex.org/C2775997480","wikidata":"https://www.wikidata.org/wiki/Q586277","display_name":"Degree (music)","level":2,"score":0.5408191680908203},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5228222608566284},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.49811244010925293},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.4690589904785156},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4369143843650818},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4270067811012268},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3812521994113922},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37071293592453003},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34787216782569885},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2631590962409973},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.25122570991516113},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-194516","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-194516","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","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":23,"referenced_works":["https://openalex.org/W1501486674","https://openalex.org/W1784617778","https://openalex.org/W1988348003","https://openalex.org/W2034692798","https://openalex.org/W2043228833","https://openalex.org/W2057266281","https://openalex.org/W2069678212","https://openalex.org/W2089685866","https://openalex.org/W2096943734","https://openalex.org/W2115403315","https://openalex.org/W2126105956","https://openalex.org/W2128053425","https://openalex.org/W2134270519","https://openalex.org/W2149466042","https://openalex.org/W2149676790","https://openalex.org/W2162854380","https://openalex.org/W2301665106","https://openalex.org/W2363300041","https://openalex.org/W2950536412","https://openalex.org/W2963214104","https://openalex.org/W2963693396","https://openalex.org/W3143107425","https://openalex.org/W6707119077"],"related_works":["https://openalex.org/W3161230432","https://openalex.org/W2997567050","https://openalex.org/W2075740387","https://openalex.org/W2168900540","https://openalex.org/W2358990940","https://openalex.org/W4367190712","https://openalex.org/W2004323682","https://openalex.org/W280458463","https://openalex.org/W1170131723","https://openalex.org/W2399035783"],"abstract_inverted_index":{"Domain":[0],"adaptation":[1,164,168],"is":[2],"an":[3],"important":[4],"branch":[5],"of":[6,26,86,95,135,174,201],"transfer":[7],"learning.":[8],"Previous":[9,138],"studies":[10,139],"have":[11,121,142,179,196],"always":[12],"taken":[13],"efforts":[14],"to":[15,102,146,157,169],"minimize":[16,48],"the":[17,23,49,61,74,84,99,117,133,136,148,154,159,171,183,191,203,212],"optimization":[18,50],"goal,":[19],"but":[20],"they":[21],"neglect":[22,73],"relative":[24,76,108],"quality":[25,109],"features":[27],"or":[28,106,113],"instances.":[29],"For":[30],"example,":[31],"a":[32,40,92,143],"classic":[33],"work":[34],"treats":[35],"different":[36,70],"instances":[37,58,82],"equally":[38],"in":[39,64,83],"degree":[41,101],"and":[42,66,71,110,165],"chooses":[43],"these":[44,57],"i":[45],"nstances":[46],"which":[47],"function":[51],"value.":[52],"This":[53],"method":[54,94,145,185,200],"will":[55,72,131],"discard":[56],"that":[59,97,123,130,182,198],"make":[60],"data":[62,68],"distribution":[63,163,167],"source":[65],"target":[67],"domain":[69,87],"instances\u2019":[75],"quality.":[77],"To":[78],"reduce":[79],"interference":[80],"between":[81,161],"process":[85],"adaptation,":[88],"we":[89,120,178],"put":[90],"forward":[91],"novel":[93],"ODA":[96,184],"uses":[98],"overlapping":[100],"measure":[103],"every":[104],"feature":[105,112],"instance\u2019s":[107],"implement":[111],"instance":[114],"reweighting.":[115],"At":[116],"same":[118],"time,":[119],"noticed":[122],"there":[124],"are":[125],"many":[126],"parameters":[127,205],"with":[128,190],"values":[129],"influence":[132],"effect":[134],"method.":[137,194,214],"do":[140],"not":[141],"reasonable":[144],"determine":[147],"parameters\u2019":[149],"values.":[150],"We":[151,195],"can":[152,206],"use":[153],"genetic":[155],"algorithm":[156],"find":[158,170],"balance":[160],"marginal":[162],"conditional":[166],"best":[172,192],"combination":[173],"multiple":[175],"parameters.":[176],"Experiments":[177],"done":[180],"verify":[181],"outperforms":[186],"by":[187],"3.26%":[188],"compared":[189],"comparison":[193],"found":[197],"our":[199],"finding":[202],"optimal":[204],"yield":[207],"more":[208],"accurate":[209],"results":[210],"than":[211],"original":[213]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-30T17:31:21.811387","created_date":"2025-10-10T00:00:00"}