{"id":"https://openalex.org/W3200574803","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533885","title":"Privacy-Preserving Convex Factorization Machine","display_name":"Privacy-Preserving Convex Factorization Machine","publication_year":2021,"publication_date":"2021-07-18","ids":{"openalex":"https://openalex.org/W3200574803","doi":"https://doi.org/10.1109/ijcnn52387.2021.9533885","mag":"3200574803"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn52387.2021.9533885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533885","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5101672960","display_name":"Jie Sun","orcid":null},"institutions":[{"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":true,"raw_author_name":"Jie Sun","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100350165","display_name":"Qi Li","orcid":"https://orcid.org/0000-0001-8776-8730"},"institutions":[{"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":"Qi Li","raw_affiliation_strings":["Institute for Network Sciences and Cyberspace & BNRist, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute for Network Sciences and Cyberspace & BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101626204","display_name":"Yong Jiang","orcid":"https://orcid.org/0000-0002-4260-1395"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Jiang","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101672960"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5517159,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9998999834060669,"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":0.9998999834060669,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9947999715805054,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9682999849319458,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.8010884523391724},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.7929465770721436},{"id":"https://openalex.org/keywords/convex-optimization","display_name":"Convex optimization","score":0.6096832752227783},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5714651346206665},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.5226007103919983},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.515568733215332},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5024271011352539},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.5022056102752686},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.49142491817474365},{"id":"https://openalex.org/keywords/convex-function","display_name":"Convex function","score":0.48209741711616516},{"id":"https://openalex.org/keywords/regular-polygon","display_name":"Regular polygon","score":0.43836042284965515},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.43403393030166626},{"id":"https://openalex.org/keywords/information-sensitivity","display_name":"Information sensitivity","score":0.4231092929840088},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.41322508454322815},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41077613830566406},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34865620732307434},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10752066969871521}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8010884523391724},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.7929465770721436},{"id":"https://openalex.org/C157972887","wikidata":"https://www.wikidata.org/wiki/Q463359","display_name":"Convex optimization","level":3,"score":0.6096832752227783},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5714651346206665},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.5226007103919983},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.515568733215332},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5024271011352539},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.5022056102752686},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.49142491817474365},{"id":"https://openalex.org/C145446738","wikidata":"https://www.wikidata.org/wiki/Q319913","display_name":"Convex function","level":3,"score":0.48209741711616516},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.43836042284965515},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.43403393030166626},{"id":"https://openalex.org/C137822555","wikidata":"https://www.wikidata.org/wiki/Q2587068","display_name":"Information sensitivity","level":2,"score":0.4231092929840088},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.41322508454322815},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41077613830566406},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34865620732307434},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10752066969871521},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn52387.2021.9533885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn52387.2021.9533885","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.4000000059604645}],"awards":[{"id":"https://openalex.org/G6827592809","display_name":null,"funder_award_id":"61572278","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W905619","https://openalex.org/W112690700","https://openalex.org/W1873763122","https://openalex.org/W1951829412","https://openalex.org/W1992926795","https://openalex.org/W2077217970","https://openalex.org/W2112380340","https://openalex.org/W2119874464","https://openalex.org/W2139750075","https://openalex.org/W2146758737","https://openalex.org/W2148825261","https://openalex.org/W2157998899","https://openalex.org/W2162379889","https://openalex.org/W2182267394","https://openalex.org/W2295739661","https://openalex.org/W2406176316","https://openalex.org/W2473418344","https://openalex.org/W2505972586","https://openalex.org/W2509235963","https://openalex.org/W2549241050","https://openalex.org/W2594311007","https://openalex.org/W2745024368","https://openalex.org/W2810715221","https://openalex.org/W2887654530","https://openalex.org/W2950943617","https://openalex.org/W2951552119","https://openalex.org/W2963004721","https://openalex.org/W2963323306","https://openalex.org/W2963999993","https://openalex.org/W2964064173","https://openalex.org/W2964984423","https://openalex.org/W2976826043","https://openalex.org/W3020097842","https://openalex.org/W3035174002","https://openalex.org/W4295910374","https://openalex.org/W6600043445","https://openalex.org/W6604483833","https://openalex.org/W6636977814","https://openalex.org/W6676639149","https://openalex.org/W6677855611","https://openalex.org/W6681291508","https://openalex.org/W6681723013","https://openalex.org/W6682942587","https://openalex.org/W6685690991","https://openalex.org/W6724478308","https://openalex.org/W6752985224"],"related_works":["https://openalex.org/W2019704260","https://openalex.org/W4304208041","https://openalex.org/W3010824232","https://openalex.org/W4212899026","https://openalex.org/W4390570329","https://openalex.org/W2795052735","https://openalex.org/W2758544064","https://openalex.org/W2603823019","https://openalex.org/W3081971900","https://openalex.org/W4286750579"],"abstract_inverted_index":{"Factorization":[0,94],"Machine":[1,95],"(FM)":[2],"significantly":[3],"improves":[4],"the":[5,9,39,48,66,71,81,111,120,126,137,142,159,168,172,176,186,194,205,222],"prediction":[6,55,87],"accuracy":[7],"of":[8,17,74,171,207],"linear":[10],"models":[11],"due":[12],"to":[13,79,110,124,135,162,203],"its":[14],"powerful":[15],"capability":[16],"feature":[18],"combination":[19],"and":[20,32,52,117,155,179,200,215],"has":[21,60],"been":[22],"widely":[23],"used":[24],"in":[25,29,141,158],"various":[26],"systems,":[27],"i.e.,":[28,153],"recommendation":[30],"systems":[31],"online":[33],"advertisement.":[34],"Convex":[35],"FM":[36,59],"further":[37],"solves":[38],"bad":[40],"local":[41],"minima":[42],"issue,":[43],"which":[44,210],"is":[45],"incurred":[46],"by":[47],"non-convex":[49],"optimization":[50,143],"problem":[51],"achieves":[53],"better":[54],"performance.":[56],"However,":[57],"convex":[58,93],"a":[61,91,131],"serious":[62],"privacy":[63,121,173],"issue":[64],"since":[65],"learning":[67,151],"process":[68],"may":[69],"reveal":[70],"sensitive":[72],"information":[73,82],"training":[75],"data.":[76],"In":[77,145],"order":[78],"mitigate":[80],"leakage":[83],"while":[84],"achieving":[85],"good":[86],"performance,":[88],"we":[89,129,147],"design":[90],"privacy-preserving":[92,164],"algorithmic":[96,104,177],"framework":[97,105,161,178],"that":[98,217],"satisfies":[99],"R\u00e9nyi":[100],"Differential":[101],"Privacy.":[102],"Our":[103],"called":[106],"Out-CFM":[107,160],"introduces":[108],"noises":[109],"learned":[112],"optimizer":[113],"at":[114],"each":[115],"round":[116],"delicately":[118],"leverages":[119],"amplification":[122],"theorem":[123],"reduce":[125],"perturbations.":[127],"Moreover,":[128],"utilize":[130],"modified":[132],"Frank-Wolfe":[133],"method":[134],"eschew":[136],"expensive":[138],"projection":[139],"operation":[140],"process.":[144],"addition,":[146],"develop":[148],"two":[149],"classical":[150],"tasks,":[152,157],"regression":[154,199],"classification":[156,201],"enable":[163],"learning.":[165],"We":[166],"provide":[167],"theoretical":[169,213],"proof":[170],"guarantee":[174],"for":[175,185,197],"derive":[180],"an":[181],"RDP-based":[182],"analytical":[183],"model":[184],"utility":[187],"analysis.":[188],"Extensive":[189],"experiments":[190],"are":[191],"performed":[192],"on":[193],"real":[195],"datasets":[196],"both":[198],"tasks":[202],"evaluate":[204],"performance":[206],"our":[208,212,218],"proposals,":[209],"validate":[211],"analysis":[214],"demonstrate":[216],"proposed":[219],"methods":[220],"outperform":[221],"baseline":[223],"methods.":[224]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
