{"id":"https://openalex.org/W2998944198","doi":"https://doi.org/10.1109/access.2020.2967348","title":"A Local-to-Global Metric Learning Framework From the Geometric Insight","display_name":"A Local-to-Global Metric Learning Framework From the Geometric Insight","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W2998944198","doi":"https://doi.org/10.1109/access.2020.2967348","mag":"2998944198"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2967348","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2967348","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08962073.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08962073.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033203506","display_name":"Yaxin Peng","orcid":"https://orcid.org/0000-0002-2983-555X"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaxin Peng","raw_affiliation_strings":["Department of Mathematics, School of Science, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-2983-555X","affiliations":[{"raw_affiliation_string":"Department of Mathematics, School of Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078373629","display_name":"Nijing Zhang","orcid":"https://orcid.org/0000-0002-9008-1216"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nijing Zhang","raw_affiliation_strings":["Department of Mathematics, School of Science, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-9008-1216","affiliations":[{"raw_affiliation_string":"Department of Mathematics, School of Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100704240","display_name":"Ying Li","orcid":"https://orcid.org/0000-0003-2103-6646"},"institutions":[{"id":"https://openalex.org/I141962983","display_name":"Shanghai University of Engineering Science","ror":"https://ror.org/0557b9y08","country_code":"CN","type":"education","lineage":["https://openalex.org/I141962983"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Li","raw_affiliation_strings":["School of Computer Engineering and Science, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-2103-6646","affiliations":[{"raw_affiliation_string":"School of Computer Engineering and Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I141962983"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063863772","display_name":"Shihui Ying","orcid":"https://orcid.org/0000-0001-9423-0146"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shihui Ying","raw_affiliation_strings":["Department of Mathematics, School of Science, Shanghai University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-9423-0146","affiliations":[{"raw_affiliation_string":"Department of Mathematics, School of Science, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.3833,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.5918437,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"8","issue":null,"first_page":"16953","last_page":"16964"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9980999827384949,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9980999827384949,"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/T11448","display_name":"Face recognition and analysis","score":0.9725000262260437,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.96670001745224,"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/metric","display_name":"Metric (unit)","score":0.6425347328186035},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.59942626953125},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5440104007720947},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5067020058631897},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5016229152679443},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.4830118417739868},{"id":"https://openalex.org/keywords/hinge-loss","display_name":"Hinge loss","score":0.47434866428375244},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4685092270374298},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.45007801055908203},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.4485163688659668},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3278259038925171},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32714349031448364},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.11755380034446716},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.09798890352249146}],"concepts":[{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6425347328186035},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.59942626953125},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5440104007720947},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5067020058631897},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5016229152679443},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.4830118417739868},{"id":"https://openalex.org/C39891107","wikidata":"https://www.wikidata.org/wiki/Q5767098","display_name":"Hinge loss","level":3,"score":0.47434866428375244},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4685092270374298},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.45007801055908203},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.4485163688659668},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3278259038925171},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32714349031448364},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.11755380034446716},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.09798890352249146},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2967348","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2967348","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08962073.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c011d59dc9b04198904f5e280354c22c","is_oa":true,"landing_page_url":"https://doaj.org/article/c011d59dc9b04198904f5e280354c22c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 16953-16964 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2967348","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2967348","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/08962073.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3207659635","display_name":null,"funder_award_id":"18010500600","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5221450027","display_name":"\u4e09\u7ef4\u533b\u5b66\u5f71\u50cf\u56fe\u8c31\u51e0\u4f55\u5efa\u6a21\u4e0e\u5185\u8574\u7b97\u6cd5\u7814\u7a76","funder_award_id":"11771276","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5920518074","display_name":null,"funder_award_id":"61573274","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6835766493","display_name":"\u5927\u8111\u5f71\u50cf\u667a\u80fd\u5206\u6790\u7684\u5c0f\u6837\u672c\u5b66\u4e60\u7406\u8bba\u4e0e\u65b9\u6cd5\u7814\u7a76","funder_award_id":"11971296","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":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2998944198.pdf","grobid_xml":"https://content.openalex.org/works/W2998944198.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W170527909","https://openalex.org/W203437397","https://openalex.org/W1546430343","https://openalex.org/W1922045146","https://openalex.org/W1973767715","https://openalex.org/W1977193486","https://openalex.org/W1986964250","https://openalex.org/W2004011892","https://openalex.org/W2014854862","https://openalex.org/W2057522815","https://openalex.org/W2065675334","https://openalex.org/W2085120256","https://openalex.org/W2096100960","https://openalex.org/W2106053110","https://openalex.org/W2113739199","https://openalex.org/W2117154949","https://openalex.org/W2124325819","https://openalex.org/W2130556178","https://openalex.org/W2136637876","https://openalex.org/W2144935315","https://openalex.org/W2155608052","https://openalex.org/W2157899944","https://openalex.org/W2158602558","https://openalex.org/W2169495281","https://openalex.org/W2187089797","https://openalex.org/W2549607029","https://openalex.org/W2555454054","https://openalex.org/W2606011186","https://openalex.org/W2615272157","https://openalex.org/W2754389237","https://openalex.org/W2768861156","https://openalex.org/W2799811029","https://openalex.org/W2802331540","https://openalex.org/W2889341738","https://openalex.org/W2950690897","https://openalex.org/W2963382234","https://openalex.org/W4210880854","https://openalex.org/W4231442273","https://openalex.org/W6607135614","https://openalex.org/W6632543029","https://openalex.org/W6671549575","https://openalex.org/W6675751002","https://openalex.org/W6676895082","https://openalex.org/W6677328822","https://openalex.org/W6680962578","https://openalex.org/W6682811751","https://openalex.org/W6683661426","https://openalex.org/W6730004014","https://openalex.org/W6738045513"],"related_works":["https://openalex.org/W1586607209","https://openalex.org/W122912556","https://openalex.org/W4312414840","https://openalex.org/W2621411691","https://openalex.org/W2271357838","https://openalex.org/W2359617897","https://openalex.org/W2556866732","https://openalex.org/W2794908468","https://openalex.org/W2328989934","https://openalex.org/W2075848805"],"abstract_inverted_index":{"Metric":[0],"plays":[1],"a":[2,43,127,186],"key":[3],"role":[4],"in":[5],"the":[6,25,36,50,62,71,75,103,109,158,194],"description":[7],"of":[8,27,39,65,164,188,198],"similarity":[9],"between":[10],"samples.":[11],"An":[12],"appropriate":[13],"metric":[14,46,67,83,92,122,129,147,168],"for":[15,162],"data":[16],"can":[17,55],"well":[18,142],"represent":[19],"their":[20],"distribution":[21],"and":[22,100,139,145,196],"further":[23],"promote":[24],"performance":[26],"learning":[28,47,93,123,130,169],"tasks.":[29],"In":[30],"this":[31],"paper,":[32],"to":[33,60],"better":[34,107],"describe":[35],"heterogeneous":[37],"distributions":[38],"data,":[40],"we":[41,69,86,116,150,177],"propose":[42,87],"semi-supervised":[44,91,140,166],"local-to-global":[45],"framework":[48,131],"from":[49],"geometric":[51],"insight.":[52],"Our":[53],"contributions":[54],"be":[56],"summarized":[57],"as:":[58],"Firstly,":[59],"enlarge":[61],"application":[63],"scope":[64],"local":[66,134],"learning,":[68],"introduce":[70],"unsupervised":[72],"information":[73],"as":[74,141,143],"regularization":[76],"term":[77],"into":[78],"our":[79,165,179,204],"smoothly":[80],"glued":[81],"nonlinear":[82,90,128,146,167],"model.":[84],"Secondly,":[85],"two":[88,96,121],"different":[89,97],"models":[94,170],"with":[95,171,181],"loss":[98,105,111],"terms,":[99],"find":[101],"that":[102,193],"smooth":[104,172],"performs":[106],"than":[108],"hinge":[110],"by":[112],"comparison":[113],"results.":[114],"Thirdly,":[115],"have":[117],"established":[118],"not":[119],"only":[120],"models,":[124],"but":[125],"also":[126],"based":[132],"on":[133,157,185],"metrics,":[135],"which":[136],"includes":[137],"supervised":[138],"linear":[144],"learning.":[148],"Moreover,":[149],"present":[151],"an":[152],"intrinsic":[153],"steepest":[154],"descent":[155],"algorithm":[156],"positive":[159],"definite":[160],"manifold":[161],"implementation":[163],"triplet":[173],"constrain":[174],"loss.":[175],"Finally,":[176],"compare":[178],"approaches":[180],"several":[182],"state-of-the-art":[183],"methods":[184],"variety":[187],"datasets.":[189],"The":[190],"results":[191],"validate":[192],"robustness":[195],"accuracy":[197],"classification":[199],"are":[200],"both":[201],"improved":[202],"under":[203],"metrics.":[205]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
