{"id":"https://openalex.org/W4387272100","doi":"https://doi.org/10.1109/tmm.2023.3321430","title":"Low-Rank Correlation Learning for Unsupervised Domain Adaptation","display_name":"Low-Rank Correlation Learning for Unsupervised Domain Adaptation","publication_year":2023,"publication_date":"2023-10-02","ids":{"openalex":"https://openalex.org/W4387272100","doi":"https://doi.org/10.1109/tmm.2023.3321430"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2023.3321430","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2023.3321430","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","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/A5032139219","display_name":"Yuwu Lu","orcid":"https://orcid.org/0000-0003-1215-4915"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuwu Lu","raw_affiliation_strings":["School of Software, South China Normal University, Foshan, China","Laboratory for Artificial Intelligence in Design, Science Park, Hong Kong"],"affiliations":[{"raw_affiliation_string":"School of Software, South China Normal University, Foshan, China","institution_ids":["https://openalex.org/I187400657"]},{"raw_affiliation_string":"Laboratory for Artificial Intelligence in Design, Science Park, Hong Kong","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026796400","display_name":"Wai Keung Wong","orcid":"https://orcid.org/0000-0002-5214-7114"},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Wai Keung Wong","raw_affiliation_strings":["School of Fashion and Textiles, The Hong Kong Polytechnic University, Kowloon, Hong Kong","Laboratory for Artificial Intelligence in Design, Science Park, Hong Kong"],"affiliations":[{"raw_affiliation_string":"School of Fashion and Textiles, The Hong Kong Polytechnic University, Kowloon, Hong Kong","institution_ids":["https://openalex.org/I14243506"]},{"raw_affiliation_string":"Laboratory for Artificial Intelligence in Design, Science Park, Hong Kong","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101456902","display_name":"Chun Yuan","orcid":"https://orcid.org/0000-0002-3590-6676"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun Yuan","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School and Peng Cheng Laboratory, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School and Peng Cheng Laboratory, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043352718","display_name":"Zhihui Lai","orcid":"https://orcid.org/0000-0002-4388-3080"},"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":"Zhihui Lai","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106943753","display_name":"Xuelong Li","orcid":"https://orcid.org/0000-0003-2924-946X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuelong Li","raw_affiliation_strings":["School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5032139219"],"corresponding_institution_ids":["https://openalex.org/I187400657"],"apc_list":null,"apc_paid":null,"fwci":3.4793,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.94087139,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"26","issue":null,"first_page":"4153","last_page":"4167"},"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":0.9643999934196472,"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":0.9007999897003174,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7668825387954712},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7033160924911499},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5761798620223999},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5506038069725037},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5402801036834717},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5066007375717163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.50030517578125},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4937048852443695},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46567460894584656},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4483345150947571},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.44299155473709106},{"id":"https://openalex.org/keywords/noisy-data","display_name":"Noisy data","score":0.4174196720123291},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3710821270942688},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1914461851119995},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12602588534355164},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08882716298103333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7668825387954712},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7033160924911499},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5761798620223999},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5506038069725037},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5402801036834717},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5066007375717163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.50030517578125},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4937048852443695},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46567460894584656},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4483345150947571},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.44299155473709106},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.4174196720123291},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3710821270942688},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1914461851119995},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12602588534355164},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08882716298103333},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2023.3321430","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2023.3321430","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5}],"awards":[{"id":"https://openalex.org/G176027883","display_name":null,"funder_award_id":"2022A1515140099","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G3627583132","display_name":null,"funder_award_id":"2023A1515012875","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G5200290963","display_name":null,"funder_award_id":"62176162","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5293734332","display_name":null,"funder_award_id":"62076129","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"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W191001584","https://openalex.org/W1934241014","https://openalex.org/W1975900269","https://openalex.org/W1997201895","https://openalex.org/W2006793117","https://openalex.org/W2096943734","https://openalex.org/W2108119513","https://openalex.org/W2112796928","https://openalex.org/W2115403315","https://openalex.org/W2144267444","https://openalex.org/W2145962650","https://openalex.org/W2149466042","https://openalex.org/W2170607218","https://openalex.org/W2214409633","https://openalex.org/W2283717164","https://openalex.org/W2614424296","https://openalex.org/W2627183927","https://openalex.org/W2759880437","https://openalex.org/W2795017224","https://openalex.org/W2803732898","https://openalex.org/W2805548989","https://openalex.org/W2805760974","https://openalex.org/W2889240504","https://openalex.org/W2897493810","https://openalex.org/W2899243711","https://openalex.org/W2903706803","https://openalex.org/W2919206487","https://openalex.org/W2923769473","https://openalex.org/W2949579163","https://openalex.org/W2962687275","https://openalex.org/W2967691516","https://openalex.org/W2974990566","https://openalex.org/W2982204955","https://openalex.org/W2984957018","https://openalex.org/W2997896449","https://openalex.org/W2998115938","https://openalex.org/W2998351473","https://openalex.org/W3001280569","https://openalex.org/W3009072794","https://openalex.org/W3041700978","https://openalex.org/W3082940395","https://openalex.org/W3106141888","https://openalex.org/W3118608800","https://openalex.org/W3119686825","https://openalex.org/W3120740533","https://openalex.org/W3145948319","https://openalex.org/W3153166695","https://openalex.org/W3159770254","https://openalex.org/W3164376598","https://openalex.org/W3196892826","https://openalex.org/W3198430326","https://openalex.org/W3200086554","https://openalex.org/W3205880411","https://openalex.org/W4205430752","https://openalex.org/W4213084105","https://openalex.org/W4246618583","https://openalex.org/W6683633756","https://openalex.org/W6713955831","https://openalex.org/W6750109254","https://openalex.org/W6757555829","https://openalex.org/W6787972765","https://openalex.org/W6929385289"],"related_works":["https://openalex.org/W3095487414","https://openalex.org/W2901026139","https://openalex.org/W2565214228","https://openalex.org/W2043065721","https://openalex.org/W4377000508","https://openalex.org/W2938008981","https://openalex.org/W2984722804","https://openalex.org/W2318195119","https://openalex.org/W2093760752","https://openalex.org/W2463534376"],"abstract_inverted_index":{"In":[0,76,89],"unsupervised":[1],"domain":[2,20,40,93,102],"adaptation":[3],"(UDA),":[4],"negative":[5,45,61,110,221],"transfer":[6,222],"is":[7,85],"one":[8],"of":[9,47,112,121,150,184],"the":[10,18,33,42,48,54,91,107,113,122,126,147,151,165,173,179,185,211],"most":[11],"challenging":[12],"problems.":[13],"Due":[14],"to":[15,73],"complex":[16],"environments,":[17],"used":[19,38],"data":[21,35,94,103,124,157,168,208],"are":[22,36,50,66,95,104,115,131,169],"always":[23],"corrupted":[24],"by":[25,64,97,133,158,172],"noise":[26,49,65,114],"or":[27],"outliers":[28],"in":[29,69,139,163],"many":[30],"applications.":[31],"If":[32],"noisy":[34,92],"directly":[37],"for":[39,53,87],"adaptation,":[41],"disturbances":[43,59,108],"and":[44,60,109,128,155,181,195,210,223],"influence":[46],"also":[51,145],"shifted":[52],"target":[55,129,156,167],"tasks.":[56],"Thus,":[57],"preventing":[58],"effects":[62,111],"caused":[63],"key":[67],"problems":[68],"UDA":[70],"that":[71,215],"need":[72],"be":[74],"addressed.":[75],"this":[77],"article,":[78],"a":[79,134,140,160,192],"low-rank":[80,98],"correlation":[81,136],"learning":[82],"(LRCL)":[83],"method":[84],"proposed":[86],"UDA.":[88],"LRCL,":[90],"recovered":[96],"learning;":[99],"then":[100],"both":[101],"cleaned.":[105],"Hence,":[106],"prevented.":[116],"The":[117],"maximized":[118],"correlated":[119],"features":[120],"clean":[123,153,166,174],"from":[125],"source":[127,154,175],"domains":[130],"learned":[132,152],"novel":[135],"regularization":[137],"term":[138],"latent":[141],"common":[142],"space.":[143],"LRCL":[144,190,198],"reduces":[146],"distribution":[148],"difference":[149],"constructing":[159],"reconstruction":[161],"term,":[162],"which":[164],"linearly":[170],"represented":[171],"data.":[176],"To":[177],"explore":[178],"temporal":[180],"structural":[182],"information":[183],"data,":[186],"we":[187],"further":[188],"extend":[189],"into":[191],"graph":[193,197],"case":[194],"propose":[196],"(GLRCL).":[199],"Extensive":[200],"experiments":[201],"have":[202],"been":[203],"conducted":[204],"on":[205],"several":[206],"public":[207],"benchmarks,":[209],"experimental":[212],"results":[213],"demonstrate":[214],"our":[216],"methods":[217],"can":[218],"effectively":[219],"prevent":[220],"obtain":[224],"better":[225],"classification":[226],"outcomes":[227],"than":[228],"other":[229],"compared":[230],"approaches.":[231]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":5}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}