{"id":"https://openalex.org/W2588646734","doi":"https://doi.org/10.1109/tkde.2017.2669193","title":"A Unified Framework for Metric Transfer Learning","display_name":"A Unified Framework for Metric Transfer Learning","publication_year":2017,"publication_date":"2017-02-14","ids":{"openalex":"https://openalex.org/W2588646734","doi":"https://doi.org/10.1109/tkde.2017.2669193","mag":"2588646734"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2017.2669193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2017.2669193","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","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/A5017102724","display_name":"Yonghui Xu","orcid":"https://orcid.org/0000-0002-1891-6186"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yonghui Xu","raw_affiliation_strings":["South China University of Technology, Guangzhou Shi, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou Shi, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082984558","display_name":"Sinno Jialin Pan","orcid":"https://orcid.org/0000-0001-6565-3836"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Sinno Jialin Pan","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101862104","display_name":"Hui Xiong","orcid":"https://orcid.org/0000-0001-6016-6465"},"institutions":[{"id":"https://openalex.org/I102322142","display_name":"Rutgers, The State University of New Jersey","ror":"https://ror.org/05vt9qd57","country_code":"US","type":"education","lineage":["https://openalex.org/I102322142"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hui Xiong","raw_affiliation_strings":["Management Science and Information Systems Department, Rutgers, State University of New Jersey, New Brunswick, NJ"],"affiliations":[{"raw_affiliation_string":"Management Science and Information Systems Department, Rutgers, State University of New Jersey, New Brunswick, NJ","institution_ids":["https://openalex.org/I102322142"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023130798","display_name":"Qingyao Wu","orcid":"https://orcid.org/0000-0002-6771-3932"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingyao Wu","raw_affiliation_strings":["South China University of Technology, Guangzhou Shi, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou Shi, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101563319","display_name":"Ronghua Luo","orcid":"https://orcid.org/0000-0001-8629-3323"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ronghua Luo","raw_affiliation_strings":["South China University of Technology, Guangzhou Shi, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou Shi, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041506521","display_name":"Huaqing Min","orcid":"https://orcid.org/0000-0003-3763-2856"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaqing Min","raw_affiliation_strings":["South China University of Technology, Guangzhou Shi, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou Shi, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087621349","display_name":"Hengjie Song","orcid":"https://orcid.org/0000-0003-4121-9466"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengjie Song","raw_affiliation_strings":["South China University of Technology, Guangzhou Shi, China"],"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou Shi, China","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5017102724"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":21.8089,"has_fulltext":false,"cited_by_count":211,"citation_normalized_percentile":{"value":0.99502818,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"29","issue":"6","first_page":"1158","last_page":"1171"},"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/T12676","display_name":"Machine Learning and ELM","score":0.9707000255584717,"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":0.9555000066757202,"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/mahalanobis-distance","display_name":"Mahalanobis distance","score":0.8935533761978149},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7514360547065735},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6658755540847778},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.6485361456871033},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5912300944328308},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.5851927995681763},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.5487070083618164},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4719252586364746},{"id":"https://openalex.org/keywords/distance-measures","display_name":"Distance measures","score":0.4657761752605438},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.45997074246406555},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4561537802219391},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44329044222831726},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3211154341697693},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17494744062423706}],"concepts":[{"id":"https://openalex.org/C1921717","wikidata":"https://www.wikidata.org/wiki/Q1334846","display_name":"Mahalanobis distance","level":2,"score":0.8935533761978149},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7514360547065735},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6658755540847778},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6485361456871033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5912300944328308},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.5851927995681763},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.5487070083618164},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4719252586364746},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.4657761752605438},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.45997074246406555},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4561537802219391},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44329044222831726},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3211154341697693},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17494744062423706},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2017.2669193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2017.2669193","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G1173061168","display_name":null,"funder_award_id":"2016A030313479","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G4428162904","display_name":null,"funder_award_id":"71671069","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8771026661","display_name":null,"funder_award_id":"M4081532.020","funder_id":"https://openalex.org/F4320320766","funder_display_name":"Nanyang Technological University"}],"funders":[{"id":"https://openalex.org/F4320309398","display_name":"California Institute of Technology","ror":"https://ror.org/05dxps055"},{"id":"https://openalex.org/F4320320766","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W22972252","https://openalex.org/W122146444","https://openalex.org/W385566662","https://openalex.org/W1495858509","https://openalex.org/W1565176903","https://openalex.org/W1593532658","https://openalex.org/W1722318740","https://openalex.org/W1834646128","https://openalex.org/W1905307128","https://openalex.org/W1916279783","https://openalex.org/W1997399503","https://openalex.org/W2027266161","https://openalex.org/W2034368206","https://openalex.org/W2060279450","https://openalex.org/W2068047518","https://openalex.org/W2090923791","https://openalex.org/W2096943734","https://openalex.org/W2100664256","https://openalex.org/W2103851188","https://openalex.org/W2105055468","https://openalex.org/W2107298017","https://openalex.org/W2112483442","https://openalex.org/W2113971713","https://openalex.org/W2115403315","https://openalex.org/W2121010533","https://openalex.org/W2122838776","https://openalex.org/W2125918842","https://openalex.org/W2130556178","https://openalex.org/W2134982367","https://openalex.org/W2136331731","https://openalex.org/W2140177290","https://openalex.org/W2149466042","https://openalex.org/W2152878561","https://openalex.org/W2153353890","https://openalex.org/W2157032359","https://openalex.org/W2158108973","https://openalex.org/W2162854380","https://openalex.org/W2163302275","https://openalex.org/W2165698076","https://openalex.org/W2169495281","https://openalex.org/W2171370495","https://openalex.org/W2212660284","https://openalex.org/W4210880854","https://openalex.org/W4250857377","https://openalex.org/W6600984841","https://openalex.org/W6605031455","https://openalex.org/W6613341870","https://openalex.org/W6629908152","https://openalex.org/W6633602821","https://openalex.org/W6637542466","https://openalex.org/W6638894083","https://openalex.org/W6639835855","https://openalex.org/W6675410418","https://openalex.org/W6675751002","https://openalex.org/W6676215431","https://openalex.org/W6676840641","https://openalex.org/W6678543856","https://openalex.org/W6681637710","https://openalex.org/W6682820082","https://openalex.org/W6684149856","https://openalex.org/W6688325169"],"related_works":["https://openalex.org/W2169159254","https://openalex.org/W149647761","https://openalex.org/W2434201124","https://openalex.org/W2183624858","https://openalex.org/W1973243276","https://openalex.org/W4310043907","https://openalex.org/W1969234006","https://openalex.org/W4390673421","https://openalex.org/W1992870039","https://openalex.org/W1992732116"],"abstract_inverted_index":{"Transfer":[0],"learning":[1,97,103],"has":[2],"been":[3,47],"proven":[4],"to":[5,59,75,100,115,128,160,168,180,193,220],"be":[6,73],"effective":[7],"for":[8,138],"the":[9,32,36,40,56,69,77,117,130,135,139,222],"problems":[10,198],"where":[11,145],"training":[12],"data":[13,20],"from":[14,21,27],"a":[15,22,94,154,173,177,228],"source":[16,37],"domain":[17,24,38],"and":[18,39,51,113,133,148,172,196,217],"test":[19],"target":[23,41,140],"are":[25,111,151],"drawn":[26],"different":[28,120,164],"distributions.":[29],"To":[30,84],"reduce":[31],"distribution":[33],"divergence":[34],"between":[35,62,82],"domain,":[42],"many":[43],"previous":[44,143],"studies":[45],"have":[46],"focused":[48],"on":[49,199,208,212],"designing":[50],"optimizing":[52],"objective":[53],"functions":[54],"with":[55,86,227],"Euclidean":[57,70],"distance":[58,71,124,150,175],"measure":[60],"dissimilarity":[61,81],"instances.":[63,83],"However,":[64],"in":[65,89,104,153,176],"some":[66],"real-world":[67,210],"applications,":[68],"may":[72],"inappropriate":[74],"capture":[76],"intrinsic":[78],"similarity":[79],"or":[80],"deal":[85],"this":[87,90],"issue,":[88],"paper,":[91],"we":[92,189],"propose":[93],"metric":[95,102],"transfer":[96,105,183],"framework":[98,156,179],"(MTLF)":[99],"encode":[101],"learning.":[106],"In":[107],"MTLF,":[108,202],"instance":[109,146,170],"weights":[110,147,171],"learned":[112,126],"exploited":[114],"bridge":[116],"distributions":[118],"of":[119,201,224,230],"domains,":[121],"while":[122],"Mahalanobis":[123,149,174],"is":[125],"simultaneously":[127],"maximize":[129],"intra-class":[131],"distances":[132,137],"minimize":[134],"inter-class":[136],"domain.":[141],"Unlike":[142],"work":[144],"trained":[152],"pipelined":[155],"that":[157],"potentially":[158],"leads":[159],"error":[161],"propagation":[162],"across":[163,184],"components,":[165],"MTLF":[166,225],"attempts":[167],"learn":[169],"parallel":[178],"make":[181],"knowledge":[182],"domains":[185],"more":[186],"effective.":[187],"Furthermore,":[188],"develop":[190],"general":[191],"solutions":[192],"both":[194],"classification":[195],"regression":[197],"top":[200],"respectively.":[203],"We":[204],"conduct":[205],"extensive":[206],"experiments":[207],"several":[209],"datasets":[211],"object":[213],"recognition,":[214,216],"handwriting":[215],"WiFi":[218],"location":[219],"verify":[221],"effectiveness":[223],"compared":[226],"number":[229],"state-of-the-art":[231],"methods.":[232]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":28},{"year":2021,"cited_by_count":33},{"year":2020,"cited_by_count":71},{"year":2019,"cited_by_count":20},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":2}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
