{"id":"https://openalex.org/W4398151535","doi":"https://doi.org/10.1109/tbdata.2024.3403393","title":"Cepe-FL: Communication-Efficient and Privacy-Enhanced Federated Learning Via Adaptive Compressive Sensing","display_name":"Cepe-FL: Communication-Efficient and Privacy-Enhanced Federated Learning Via Adaptive Compressive Sensing","publication_year":2024,"publication_date":"2024-05-20","ids":{"openalex":"https://openalex.org/W4398151535","doi":"https://doi.org/10.1109/tbdata.2024.3403393"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2024.3403393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2024.3403393","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/A5102972220","display_name":"Ye Liu","orcid":"https://orcid.org/0009-0004-4603-5337"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Liu","raw_affiliation_strings":["School of Computer Science &#x0026; Technology, Donghua University, Shanghai, China","School of Computer Science &amp; Technology, Donghua University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0004-4603-5337","affiliations":[{"raw_affiliation_string":"School of Computer Science &#x0026; Technology, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]},{"raw_affiliation_string":"School of Computer Science &amp; Technology, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013173652","display_name":"Shan Chang","orcid":"https://orcid.org/0000-0002-5253-2549"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Chang","raw_affiliation_strings":["School of Computer Science &#x0026; Technology, Donghua University, Shanghai, China","School of Computer Science &amp; Technology, Donghua University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-5253-2549","affiliations":[{"raw_affiliation_string":"School of Computer Science &#x0026; Technology, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]},{"raw_affiliation_string":"School of Computer Science &amp; Technology, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yiqi Liu","orcid":"https://orcid.org/0009-0005-8717-068X"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiqi Liu","raw_affiliation_strings":["School of Computer Science &#x0026; Technology, Donghua University, Shanghai, China","School of Computer Science &amp; Technology, Donghua University, Shanghai, China"],"raw_orcid":"https://orcid.org/0009-0005-8717-068X","affiliations":[{"raw_affiliation_string":"School of Computer Science &#x0026; Technology, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]},{"raw_affiliation_string":"School of Computer Science &amp; Technology, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181326427"],"apc_list":null,"apc_paid":null,"fwci":0.2778,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58598174,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"11","issue":"5","first_page":"2119","last_page":"2134"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9993000030517578,"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":0.9993000030517578,"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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9891999959945679,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11609","display_name":"Geophysical Methods and Applications","score":0.9829000234603882,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7367663979530334},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6286779642105103},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5992265939712524},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5477920174598694},{"id":"https://openalex.org/keywords/notation","display_name":"Notation","score":0.4866703152656555},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.44247251749038696},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4217208921909332},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3933427035808563},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3481229543685913},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16245850920677185}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7367663979530334},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6286779642105103},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5992265939712524},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5477920174598694},{"id":"https://openalex.org/C45357846","wikidata":"https://www.wikidata.org/wiki/Q2001982","display_name":"Notation","level":2,"score":0.4866703152656555},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.44247251749038696},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4217208921909332},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3933427035808563},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3481229543685913},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16245850920677185},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2024.3403393","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2024.3403393","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":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.44999998807907104}],"awards":[{"id":"https://openalex.org/G6947671634","display_name":"\u6297\u6a21\u578b\u6bd2\u5316\u4e0e\u9690\u79c1\u6cc4\u9732\u7684\u8054\u5408\u5b66\u4e60\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61972081","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G785799366","display_name":null,"funder_award_id":"2232023Y-01","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G835335910","display_name":null,"funder_award_id":"22ZR1400200","funder_id":"https://openalex.org/F4320309612","funder_display_name":"Natural Science Foundation of Shanghai"}],"funders":[{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"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":33,"referenced_works":["https://openalex.org/W1977252496","https://openalex.org/W2007339694","https://openalex.org/W2015418199","https://openalex.org/W2092392156","https://openalex.org/W2109357213","https://openalex.org/W2127271355","https://openalex.org/W2145096794","https://openalex.org/W2160547390","https://openalex.org/W2405578611","https://openalex.org/W2535690855","https://openalex.org/W2591882872","https://openalex.org/W2606891064","https://openalex.org/W2884943453","https://openalex.org/W2930926105","https://openalex.org/W2941578813","https://openalex.org/W2963456518","https://openalex.org/W2970408908","https://openalex.org/W2978015420","https://openalex.org/W2983140679","https://openalex.org/W2989289980","https://openalex.org/W3107725882","https://openalex.org/W3111009493","https://openalex.org/W3129329365","https://openalex.org/W3156794839","https://openalex.org/W3162286130","https://openalex.org/W3162353295","https://openalex.org/W3164900515","https://openalex.org/W4250955649","https://openalex.org/W4280575929","https://openalex.org/W4327796923","https://openalex.org/W4363649017","https://openalex.org/W4386072282","https://openalex.org/W4387784496"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W2504004674","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W1881631164","https://openalex.org/W1987679298","https://openalex.org/W2963177394","https://openalex.org/W4313359513","https://openalex.org/W1976264255"],"abstract_inverted_index":{"Model":[0],"updates":[1],"are":[2,39,147],"exchanged":[3],"between":[4,128],"server(s)":[5],"and":[6,29,41,67,130,158,167,179,189],"participants":[7],"in":[8,15,99,137,174,201],"Federated":[9],"Learning":[10],"(FL),":[11],"which":[12,75],"can":[13,42,47,194],"result":[14],"excessive":[16],"delay,":[17],"especially":[18],"for":[19],"large":[20],"models.":[21],"Existing":[22],"communication-efficient":[23,162],"FL":[24],"approaches":[25,163],"such":[26],"as":[27],"quantization":[28],"top-k":[30],"sampling":[31],"apply":[32],"compression":[33,72,116],"to":[34,51,79,87,107,120],"gradients":[35,38,66],"assuming":[36],"that":[37],"sparse":[40,85],"tolerate":[43],"small":[44],"deviations.":[45],"This":[46],"hardly":[48],"be":[49],"applied":[50],"down-link":[52],"transmission.":[53],"In":[54],"this":[55],"work,":[56],"we":[57],"employ":[58],"compressive":[59],"sensing":[60],"on":[61,153],"model":[62,82,94,131],"parameters":[63,83],"instead":[64],"of":[65,199],"propose":[68],"a":[69],"two-way":[70],"adaptive":[71],"scheme,":[73],"Cepe-FL,":[74],"exploits":[76],"dictionary":[77],"learning":[78],"project":[80],"non-sparse":[81],"into":[84],"representations":[86],"ensure":[88],"reconstruction":[89,95],"accuracy.":[90],"Cepe-FL":[91,113,169,193],"supports":[92],"joint":[93],"with":[96,160,203],"drastic":[97],"reduction":[98],"computational":[100],"complexity":[101],"from":[102],"<inline-formula":[103,108],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[104,109],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[105,110],"notation=\"LaTeX\">$O(n)$</tex-math></inline-formula>":[106],"notation=\"LaTeX\">$O(1)$</tex-math></inline-formula>":[111],".":[112],"adjusts":[114],"the":[115,121,125,171,190],"ratio":[117,198],"adaptively":[118],"according":[119],"training":[122],"loss,":[123],"achieving":[124],"best":[126,172],"trade-off":[127],"communication":[129],"precision.":[132],"Furthermore,":[133],"it":[134],"demonstrates":[135],"efficacy":[136],"defending":[138],"against":[139],"membership":[140,186],"inference":[141,187,200],"attacks":[142],"since":[143],"only":[144],"compressed":[145],"models":[146],"exchanged.":[148],"We":[149,182],"conduct":[150],"extensive":[151],"experiments":[152],"three":[154,161],"image":[155],"classification":[156],"tasks":[157,176],"compare":[159],"including":[164],"FedPAQ,":[165],"FedAvg":[166],"T-FedAvg.":[168],"presents":[170],"performance":[173],"all":[175],"under":[177],"IID":[178],"non-IID":[180],"scenarios.":[181],"also":[183],"implement":[184],"white-box":[185],"attacks,":[188],"results":[191],"show":[192],"significantly":[195],"suppress":[196],"success":[197],"comparison":[202],"other":[204],"approaches.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}