{"id":"https://openalex.org/W4398150845","doi":"https://doi.org/10.1109/tbdata.2024.3403386","title":"A Hybrid Self-Supervised Learning Framework for Vertical Federated Learning","display_name":"A Hybrid Self-Supervised Learning Framework for Vertical Federated Learning","publication_year":2024,"publication_date":"2024-05-20","ids":{"openalex":"https://openalex.org/W4398150845","doi":"https://doi.org/10.1109/tbdata.2024.3403386"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2024.3403386","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2024.3403386","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"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 Big Data","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/A5081652296","display_name":"Yuanqin He","orcid":"https://orcid.org/0000-0001-5468-6608"},"institutions":[{"id":"https://openalex.org/I4210093114","display_name":"Shenzhen Weiguang Biological Products (China)","ror":"https://ror.org/00hdm6c37","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210093114"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuanqin He","raw_affiliation_strings":["AI Group, Webank, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-5468-6608","affiliations":[{"raw_affiliation_string":"AI Group, Webank, Shenzhen, China","institution_ids":["https://openalex.org/I4210093114"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yan Kang","orcid":"https://orcid.org/0000-0002-2016-9503"},"institutions":[{"id":"https://openalex.org/I4210093114","display_name":"Shenzhen Weiguang Biological Products (China)","ror":"https://ror.org/00hdm6c37","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210093114"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Kang","raw_affiliation_strings":["AI Group, Webank, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-2016-9503","affiliations":[{"raw_affiliation_string":"AI Group, Webank, Shenzhen, China","institution_ids":["https://openalex.org/I4210093114"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5098723545","display_name":"Xinyuan Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyuan Zhao","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-1978-6854","affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiahuan Luo","orcid":"https://orcid.org/0000-0001-5742-1330"},"institutions":[{"id":"https://openalex.org/I4210093114","display_name":"Shenzhen Weiguang Biological Products (China)","ror":"https://ror.org/00hdm6c37","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210093114"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahuan Luo","raw_affiliation_strings":["AI Group, Webank, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-5742-1330","affiliations":[{"raw_affiliation_string":"AI Group, Webank, Shenzhen, China","institution_ids":["https://openalex.org/I4210093114"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100373580","display_name":"Lixin Fan","orcid":"https://orcid.org/0000-0002-8162-7096"},"institutions":[{"id":"https://openalex.org/I4210093114","display_name":"Shenzhen Weiguang Biological Products (China)","ror":"https://ror.org/00hdm6c37","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210093114"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixin Fan","raw_affiliation_strings":["AI Group, Webank, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-8162-7096","affiliations":[{"raw_affiliation_string":"AI Group, Webank, Shenzhen, China","institution_ids":["https://openalex.org/I4210093114"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101944724","display_name":"Yuxing Han","orcid":"https://orcid.org/0000-0003-2558-8966"},"institutions":[{"id":"https://openalex.org/I3131625388","display_name":"University Town of Shenzhen","ror":"https://ror.org/05f5j6225","country_code":"CN","type":"education","lineage":["https://openalex.org/I3131625388"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxing Han","raw_affiliation_strings":["Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2558-8966","affiliations":[{"raw_affiliation_string":"Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I3131625388","https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100636286","display_name":"Qiang Yang","orcid":"https://orcid.org/0000-0001-5059-8360"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Qiang Yang","raw_affiliation_strings":["Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong, China"],"raw_orcid":"https://orcid.org/0000-0001-5059-8360","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Hong Kong, China","institution_ids":["https://openalex.org/I200769079"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5081652296"],"corresponding_institution_ids":["https://openalex.org/I4210093114"],"apc_list":null,"apc_paid":null,"fwci":4.967,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.9568631,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"11","issue":"5","first_page":"2210","last_page":"2223"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9951000213623047,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9951000213623047,"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":0.8425931930541992},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44838663935661316},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36978816986083984}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8425931930541992},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44838663935661316},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36978816986083984}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2024.3403386","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2024.3403386","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"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 Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1135894947","display_name":null,"funder_award_id":"62206154","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":27,"referenced_works":["https://openalex.org/W1920022804","https://openalex.org/W2007972815","https://openalex.org/W2903890850","https://openalex.org/W2989885118","https://openalex.org/W3035524453","https://openalex.org/W3088573320","https://openalex.org/W3093331990","https://openalex.org/W3110068734","https://openalex.org/W3164712068","https://openalex.org/W3171007011","https://openalex.org/W3182158470","https://openalex.org/W3192072825","https://openalex.org/W3193756050","https://openalex.org/W3204874618","https://openalex.org/W3208338073","https://openalex.org/W4214626077","https://openalex.org/W4224943538","https://openalex.org/W4280588203","https://openalex.org/W4283260449","https://openalex.org/W4285011395","https://openalex.org/W4285049389","https://openalex.org/W4285404750","https://openalex.org/W4285821506","https://openalex.org/W4296207781","https://openalex.org/W4312592506","https://openalex.org/W4320839683","https://openalex.org/W4391250546"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"Vertical":[0],"federated":[1],"learning":[2,113],"(VFL),":[3],"a":[4,77,141],"variant":[5],"of":[6,22,57,69,92,103,115,131,166],"Federated":[7,78],"Learning":[8,81],"(FL),":[9],"has":[10],"recently":[11],"drawn":[12],"increasing":[13],"attention":[14],"as":[15,41,140],"the":[16,19,55,67,70,111,116,129,132,190,195],"VFL":[17,34,117,178],"matches":[18],"enterprises'":[20],"demands":[21],"leveraging":[23],"more":[24],"valuable":[25],"features":[26,124],"to":[27,50,109,127],"achieve":[28],"better":[29],"model":[30,134,137],"performance.":[31],"However,":[32],"conventional":[33],"methods":[35,155],"may":[36],"run":[37],"into":[38],"data":[39,64,101],"deficiency":[40,65],"they":[42],"exploit":[43],"only":[44],"aligned":[45,94],"and":[46,59,97],"labeled":[47],"samples":[48,61,93,105],"(belonging":[49],"different":[51],"parties),":[52],"leaving":[53],"often":[54],"majority":[56],"unaligned":[58,104],"unlabeled":[60],"unused.":[62],"The":[63,180],"hampers":[66],"effort":[68],"federation.":[71],"In":[72],"this":[73],"work,":[74],"we":[75],"propose":[76],"Hybrid":[79],"Self-Supervised":[80],"framework,":[82,142],"named":[83],"FedHSSL,":[84,139],"that":[85,153],"utilizes":[86],"cross-party":[87],"views":[88,99],"(i.e.,":[89,100],"dispersed":[90],"features)":[91],"among":[95],"parties":[96,126],"local":[98],"augmentation)":[102],"within":[106],"each":[107],"party":[108],"improve":[110],"representation":[112],"capability":[114],"joint":[118,133],"model.":[119],"FedHSSL":[120,154,167,188],"further":[121],"exploits":[122],"invariant":[123],"across":[125],"boost":[128],"performance":[130],"through":[135],"partial":[136],"aggregation.":[138],"can":[143],"work":[144],"with":[145,185,201],"various":[146],"representative":[147],"SSL":[148],"methods.":[149],"We":[150,161],"empirically":[151],"demonstrate":[152],"outperform":[156],"baselines":[157],"by":[158],"large":[159],"margins.":[160],"provide":[162],"an":[163],"in-depth":[164],"analysis":[165],"regarding":[168],"label":[169,197],"leakage,":[170],"which":[171],"is":[172,204],"rarely":[173],"investigated":[174],"in":[175],"existing":[176],"self-supervised":[177],"works.":[179],"experimental":[181],"results":[182],"show":[183],"that,":[184],"proper":[186],"protection,":[187],"achieves":[189],"best":[191],"privacy-utility":[192],"trade-off":[193],"against":[194],"state-of-the-art":[196],"inference":[198],"attack":[199],"compared":[200],"baselines.":[202],"Code":[203],"available":[205],"at":[206],"<uri":[207],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[208],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/jorghyq2016/FedHSSL</uri>":[209],".":[210]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}