{"id":"https://openalex.org/W4313855666","doi":"https://doi.org/10.1109/tmm.2023.3235526","title":"Deep Robust Low Rank Correlation With Unifying Clustering Structure for Cross Domain Adaptation","display_name":"Deep Robust Low Rank Correlation With Unifying Clustering Structure for Cross Domain Adaptation","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4313855666","doi":"https://doi.org/10.1109/tmm.2023.3235526"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2023.3235526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2023.3235526","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/A5015596649","display_name":"Xiang\u2010Jun Shen","orcid":"https://orcid.org/0000-0002-3359-8972"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiang-Jun Shen","raw_affiliation_strings":["School of Computer Science and Communication Engineering, JiangSu University, JiangSu, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Communication Engineering, JiangSu University, JiangSu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082645019","display_name":"Yanan Cai","orcid":"https://orcid.org/0000-0002-0856-4404"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanan Cai","raw_affiliation_strings":["School of Computer Science and Communication Engineering, JiangSu University, JiangSu, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Communication Engineering, JiangSu University, JiangSu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068969296","display_name":"Stanley Ebhohimhen Abhadiomhen","orcid":"https://orcid.org/0000-0002-9509-1915"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]},{"id":"https://openalex.org/I11892038","display_name":"University of Nigeria","ror":"https://ror.org/01sn1yx84","country_code":"NG","type":"education","lineage":["https://openalex.org/I11892038"]}],"countries":["CN","NG"],"is_corresponding":false,"raw_author_name":"Stanley Ebhohimhen Abhadiomhen","raw_affiliation_strings":["School of Computer Science and Communication Engineering, JiangSu University, JiangSu, China","Department of Computer Science, University of Nigeria, Nsukka, Nigeria"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Communication Engineering, JiangSu University, JiangSu, China","institution_ids":["https://openalex.org/I115592961"]},{"raw_affiliation_string":"Department of Computer Science, University of Nigeria, Nsukka, Nigeria","institution_ids":["https://openalex.org/I11892038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101720700","display_name":"Zhifeng Liu","orcid":"https://orcid.org/0000-0002-4664-1140"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhifeng Liu","raw_affiliation_strings":["School of Computer Science and Communication Engineering, JiangSu University, JiangSu, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Communication Engineering, JiangSu University, JiangSu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046419939","display_name":"Yongzhao Zhan","orcid":"https://orcid.org/0000-0001-7475-2895"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong-Zhao Zhan","raw_affiliation_strings":["School of Computer Science and Communication Engineering, JiangSu University, JiangSu, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Communication Engineering, JiangSu University, JiangSu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100728569","display_name":"Jianping Fan","orcid":"https://orcid.org/0000-0003-2290-1785"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianping Fan","raw_affiliation_strings":["AI Lab, Lenovo Research, Charlotte, USA"],"affiliations":[{"raw_affiliation_string":"AI Lab, Lenovo Research, Charlotte, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5015596649"],"corresponding_institution_ids":["https://openalex.org/I115592961"],"apc_list":null,"apc_paid":null,"fwci":0.2477,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.66445252,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"25","issue":null,"first_page":"8334","last_page":"8345"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9904000163078308,"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/T11316","display_name":"Mycobacterium research and diagnosis","score":0.9648000001907349,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"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":0.8280177116394043},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.715410590171814},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6017016768455505},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5573675036430359},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5428389310836792},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5187378525733948},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48978757858276367},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4859377443790436},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.45720866322517395},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4102725684642792},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3266619145870209},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32526034116744995},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11153843998908997},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10046231746673584}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8280177116394043},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.715410590171814},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6017016768455505},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5573675036430359},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5428389310836792},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5187378525733948},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48978757858276367},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4859377443790436},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.45720866322517395},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4102725684642792},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3266619145870209},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32526034116744995},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11153843998908997},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10046231746673584},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2023.3235526","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2023.3235526","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W881606563","https://openalex.org/W1722318740","https://openalex.org/W2012756207","https://openalex.org/W2018096278","https://openalex.org/W2081863860","https://openalex.org/W2089609272","https://openalex.org/W2089685866","https://openalex.org/W2103972604","https://openalex.org/W2123576058","https://openalex.org/W2133556223","https://openalex.org/W2142674578","https://openalex.org/W2240559667","https://openalex.org/W2296398754","https://openalex.org/W2312004824","https://openalex.org/W2395579298","https://openalex.org/W2478454054","https://openalex.org/W2577472518","https://openalex.org/W2584117868","https://openalex.org/W2614424296","https://openalex.org/W2627183927","https://openalex.org/W2741178908","https://openalex.org/W2898541610","https://openalex.org/W2913340405","https://openalex.org/W2950692821","https://openalex.org/W2962690307","https://openalex.org/W2963240485","https://openalex.org/W2963532621","https://openalex.org/W2997951773","https://openalex.org/W3035519852","https://openalex.org/W3109898199","https://openalex.org/W3166547620","https://openalex.org/W3168084736","https://openalex.org/W3176720610","https://openalex.org/W3177151237","https://openalex.org/W3202165894","https://openalex.org/W4292363360","https://openalex.org/W4312768455","https://openalex.org/W6603183647","https://openalex.org/W6603760306","https://openalex.org/W6631190155","https://openalex.org/W6631216910","https://openalex.org/W6681588610","https://openalex.org/W6682889407","https://openalex.org/W6735050833","https://openalex.org/W6738597727","https://openalex.org/W6744043827","https://openalex.org/W6748312029","https://openalex.org/W6754528357"],"related_works":["https://openalex.org/W4389474468","https://openalex.org/W4300172004","https://openalex.org/W2955455867","https://openalex.org/W4321649381","https://openalex.org/W3180787869","https://openalex.org/W2997645659","https://openalex.org/W3203792196","https://openalex.org/W4295929828","https://openalex.org/W3156096827","https://openalex.org/W4287890001"],"abstract_inverted_index":{"Cross":[0],"domain":[1,11,21,40,85,163,183],"adaptation":[2,184],"aims":[3],"to":[4,34,70,125],"improve":[5,35,158],"the":[6,9,28,36,56,72,80,90,100,117,126,142,145,153,159],"performance":[7,160],"of":[8,17,38,59,83,93,144,155,161],"target":[10,77],"model":[12,69,140,178],"by":[13],"making":[14],"full":[15],"use":[16],"information":[18,25],"rich":[19],"source":[20,75],"samples.":[22],"However,":[23],"as":[24],"becomes":[26],"richer,":[27],"noise":[29,156],"also":[30],"increases.":[31],"In":[32,129],"order":[33,98],"reliability":[37],"cross":[39,84,162,182],"adaptation,":[41],"we":[42,64,109,132],"propose":[43],"a":[44,66,105,111,134],"novel":[45],"method":[46],"based":[47],"on":[48,167],"deep":[49,135],"robust":[50,67,136],"low":[51,137],"rank":[52,138],"correlation.":[53],"Borrowed":[54],"from":[55],"traditional":[57],"idea":[58],"Canonical":[60],"Correlation":[61],"Analysis":[62],"(CCA),":[63],"developed":[65],"correlation":[68,73,139],"maximize":[71],"between":[74],"and":[76,123,157,173],"domains.":[78],"Also,":[79],"low-rank":[81],"characteristics":[82],"data":[86,102],"can":[87,103,120,150],"effectively":[88,151],"reduce":[89,152],"negative":[91],"influence":[92,154],"noisy":[94],"data.":[95],"Furthermore,":[96],"in":[97],"that":[99,176],"cross-domain":[101],"share":[104],"unifying":[106,127,146],"clustering":[107,147],"structure,":[108,148],"introduced":[110],"common":[112],"Laplacian":[113],"affinity":[114],"structure.":[115,128],"Then":[116],"learned":[118],"features":[119],"be":[121],"smoothed":[122],"aligned":[124],"this":[130],"way,":[131],"obtain":[133],"with":[141],"help":[143],"which":[149],"adaptation.":[164],"Experimental":[165],"results":[166],"three":[168],"datasets":[169],"including":[170],"Office-31,":[171],"ImageCLEF-DA":[172],"Office-Home":[174],"show":[175],"our":[177],"significantly":[179],"outperforms":[180],"state-of-the-art":[181],"methods.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}