{"id":"https://openalex.org/W4293057192","doi":"https://doi.org/10.1109/tnnls.2022.3199619","title":"Semantic Correlation Transfer for Heterogeneous Domain Adaptation","display_name":"Semantic Correlation Transfer for Heterogeneous Domain Adaptation","publication_year":2022,"publication_date":"2022-08-25","ids":{"openalex":"https://openalex.org/W4293057192","doi":"https://doi.org/10.1109/tnnls.2022.3199619","pmid":"https://pubmed.ncbi.nlm.nih.gov/36006880"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3199619","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3199619","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/A5100434217","display_name":"Ying Zhao","orcid":"https://orcid.org/0000-0002-7927-4906"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ying Zhao","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100415954","display_name":"Shuang Li","orcid":"https://orcid.org/0000-0003-1910-7812"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Li","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1910-7812","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Rui Zhang","orcid":"https://orcid.org/0000-0001-6358-0055"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6358-0055","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102923184","display_name":"Chi Harold Liu","orcid":"https://orcid.org/0000-0002-0252-329X"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chi Harold Liu","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0252-329X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028260055","display_name":"Weipeng Cao","orcid":"https://orcid.org/0000-0003-2414-6066"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weipeng Cao","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2414-6066","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073006299","display_name":"Xizhao Wang","orcid":"https://orcid.org/0000-0001-6036-4728"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xizhao Wang","raw_affiliation_strings":["Big Data Institute, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-6036-4728","affiliations":[{"raw_affiliation_string":"Big Data Institute, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I4210099586","https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":null,"display_name":"Song Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I1299457549","display_name":"Civil Aviation Administration of China","ror":"https://ror.org/05gfwht30","country_code":"CN","type":"government","lineage":["https://openalex.org/I1299457549","https://openalex.org/I4210127216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song Tian","raw_affiliation_strings":["TravelSky Technology Limited, Beijing, China","Beijing Engineering Research Center of Civil Aviation Big Data, Beijing, China","Key Laboratory of Intelligent Passenger Service of Civil Aviation, Civil Aviation Administration of China (CAAC), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TravelSky Technology Limited, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Beijing Engineering Research Center of Civil Aviation Big Data, Beijing, China","institution_ids":[]},{"raw_affiliation_string":"Key Laboratory of Intelligent Passenger Service of Civil Aviation, Civil Aviation Administration of China (CAAC), Beijing, China","institution_ids":["https://openalex.org/I1299457549"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100434217"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":1.5261,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.85421466,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"36","issue":"3","first_page":"4233","last_page":"4245"},"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":0.9998000264167786,"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":0.9998000264167786,"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":0.9904999732971191,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9045000076293945,"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":0.6111605763435364},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5815293788909912},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.573510468006134},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5653095245361328},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5428287386894226},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.49826836585998535},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.49775388836860657},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.49363768100738525},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.4801573157310486},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.46903952956199646},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.46247684955596924},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.4528459310531616},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3799603581428528},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.37456458806991577},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3533327579498291},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24623888731002808},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.09420257806777954}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6111605763435364},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5815293788909912},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.573510468006134},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5653095245361328},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5428287386894226},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.49826836585998535},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.49775388836860657},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.49363768100738525},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.4801573157310486},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.46903952956199646},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.46247684955596924},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.4528459310531616},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3799603581428528},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.37456458806991577},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3533327579498291},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24623888731002808},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.09420257806777954},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3199619","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3199619","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:36006880","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36006880","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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7300000190734863}],"awards":[{"id":"https://openalex.org/G2600243670","display_name":null,"funder_award_id":"U21A20519","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4762857569","display_name":null,"funder_award_id":"61902028","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":76,"referenced_works":["https://openalex.org/W46086471","https://openalex.org/W1565327149","https://openalex.org/W1576445103","https://openalex.org/W1677409904","https://openalex.org/W1722318740","https://openalex.org/W1932600547","https://openalex.org/W1970942930","https://openalex.org/W1981658663","https://openalex.org/W2007972815","https://openalex.org/W2009668020","https://openalex.org/W2046385669","https://openalex.org/W2050398567","https://openalex.org/W2090923791","https://openalex.org/W2096943734","https://openalex.org/W2100664256","https://openalex.org/W2108598243","https://openalex.org/W2115403315","https://openalex.org/W2124776405","https://openalex.org/W2124961556","https://openalex.org/W2125865219","https://openalex.org/W2131953535","https://openalex.org/W2153867457","https://openalex.org/W2163345210","https://openalex.org/W2165698076","https://openalex.org/W2170607218","https://openalex.org/W2194775991","https://openalex.org/W2214409633","https://openalex.org/W2294202617","https://openalex.org/W2317413155","https://openalex.org/W2326626448","https://openalex.org/W2342085406","https://openalex.org/W2408012181","https://openalex.org/W2422697180","https://openalex.org/W2508804393","https://openalex.org/W2519397578","https://openalex.org/W2740361506","https://openalex.org/W2803106019","https://openalex.org/W2808408933","https://openalex.org/W2808635635","https://openalex.org/W2889945482","https://openalex.org/W2892946488","https://openalex.org/W2893630558","https://openalex.org/W2895281799","https://openalex.org/W2946169958","https://openalex.org/W2946948585","https://openalex.org/W2955547856","https://openalex.org/W2962687275","https://openalex.org/W2962898354","https://openalex.org/W2963107255","https://openalex.org/W2963446712","https://openalex.org/W2963466847","https://openalex.org/W2969893028","https://openalex.org/W2969985801","https://openalex.org/W2978573218","https://openalex.org/W2981682949","https://openalex.org/W2991405316","https://openalex.org/W2999216888","https://openalex.org/W3018638193","https://openalex.org/W3047379413","https://openalex.org/W3092755432","https://openalex.org/W3097643695","https://openalex.org/W3131415659","https://openalex.org/W4295150927","https://openalex.org/W6633602821","https://openalex.org/W6633949838","https://openalex.org/W6634343353","https://openalex.org/W6638894083","https://openalex.org/W6639480849","https://openalex.org/W6677741084","https://openalex.org/W6679847558","https://openalex.org/W6680922216","https://openalex.org/W6684191040","https://openalex.org/W6733525777","https://openalex.org/W6761139768","https://openalex.org/W6766978945","https://openalex.org/W6774861611"],"related_works":["https://openalex.org/W2487162673","https://openalex.org/W2793211469","https://openalex.org/W2949152769","https://openalex.org/W4372354731","https://openalex.org/W2942366970","https://openalex.org/W2807634898","https://openalex.org/W1692008701","https://openalex.org/W2597588799","https://openalex.org/W4283211831","https://openalex.org/W2798287483"],"abstract_inverted_index":{"Heterogeneous":[0],"domain":[1,15,20,38,90,102],"adaptation":[2,55,180],"(HDA)":[3],"is":[4],"expected":[5],"to":[6,16,30,60,86,103,128,151,162],"achieve":[7],"effective":[8],"knowledge":[9,98,158],"transfer":[10,70,152],"from":[11],"a":[12,17,66,166],"label-rich":[13],"source":[14,101,112,155],"heterogeneous":[18],"target":[19,104,163],"with":[21],"scarce":[22],"labeled":[23],"data.":[24],"Most":[25],"prior":[26],"HDA":[27,189,208],"methods":[28],"strive":[29],"align":[31],"the":[32,43,53,79,88,95,100,107,116,129,135,141,153,168,179,199],"cross-domain":[33],"feature":[34,130,169],"distributions":[35,83],"by":[36,105],"learning":[37],"invariant":[39],"representations":[40],"without":[41],"considering":[42],"intrinsic":[44],"semantic":[45,68,156],"correlations":[46],"among":[47,159],"categories,":[48],"which":[49,75],"inevitably":[50],"results":[51],"in":[52,148],"suboptimal":[54],"performance":[56],"across":[57,111],"domains.":[58],"Therefore,":[59],"address":[61],"this":[62],"issue,":[63],"we":[64,139],"propose":[65],"novel":[67],"correlation":[69,97,157],"(SCT)":[71],"method":[72],"for":[73],"HDA,":[74],"not":[76],"only":[77],"matches":[78],"marginal":[80],"and":[81,113,118,125,171,184,195],"conditional":[82],"between":[84],"domains":[85,150],"mitigate":[87],"large":[89],"discrepancy,":[91],"but":[92],"also":[93],"transfers":[94],"category":[96,172],"underlying":[99],"maximizing":[106],"pairwise":[108],"class":[109],"similarity":[110,143],"target.":[114],"Technically,":[115],"domainwise":[117],"classwise":[119,137],"centroids":[120],"(prototypes)":[121],"are":[122],"first":[123],"computed":[124],"aligned":[126],"according":[127],"embeddings.":[131],"Then,":[132],"based":[133],"on":[134,187],"derived":[136],"prototypes,":[138],"leverage":[140],"cosine":[142],"of":[144,201],"each":[145],"two":[146],"classes":[147],"both":[149],"supervised":[154],"different":[160],"categories":[161],"effectively.":[164],"As":[165],"result,":[167],"transferability":[170],"discriminability":[173],"can":[174],"be":[175],"simultaneously":[176],"improved":[177],"during":[178],"process.":[181],"Comprehensive":[182],"experiments":[183],"ablation":[185],"studies":[186],"standard":[188],"tasks,":[190],"such":[191],"as":[192],"text-to-image,":[193],"image-to-image,":[194],"text-to-text,":[196],"have":[197],"demonstrated":[198],"superiority":[200],"our":[202],"proposed":[203],"SCT":[204],"against":[205],"several":[206],"state-of-the-art":[207],"methods.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}