{"id":"https://openalex.org/W2919337578","doi":"https://doi.org/10.1109/infocom.2019.8737494","title":"Differentially-Private Deep Learning from an optimization Perspective","display_name":"Differentially-Private Deep Learning from an optimization Perspective","publication_year":2019,"publication_date":"2019-04-01","ids":{"openalex":"https://openalex.org/W2919337578","doi":"https://doi.org/10.1109/infocom.2019.8737494","mag":"2919337578"},"language":"en","primary_location":{"id":"doi:10.1109/infocom.2019.8737494","is_oa":false,"landing_page_url":"https://doi.org/10.1109/infocom.2019.8737494","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE INFOCOM 2019 - IEEE Conference on Computer Communications","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/A5018175815","display_name":"Liyao Xiang","orcid":"https://orcid.org/0000-0003-0165-4930"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liyao Xiang","raw_affiliation_strings":["John Hopcroft Center for Computer Science, Shanghai Jiao Tong University"],"affiliations":[{"raw_affiliation_string":"John Hopcroft Center for Computer Science, Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101176820","display_name":"Jingbo Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jingbo Yang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Toronto","[Department of Electrical and Computer Engineering, University of Toronto]"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Toronto","institution_ids":["https://openalex.org/I185261750"]},{"raw_affiliation_string":"[Department of Electrical and Computer Engineering, University of Toronto]","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083596391","display_name":"Baochun Li","orcid":"https://orcid.org/0000-0003-2404-0974"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Baochun Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Toronto","[Department of Electrical and Computer Engineering, University of Toronto]"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Toronto","institution_ids":["https://openalex.org/I185261750"]},{"raw_affiliation_string":"[Department of Electrical and Computer Engineering, University of Toronto]","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5018175815"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":3.0803,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.93270801,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"559","last_page":"567"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":1.0,"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":1.0,"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":0.9941999912261963,"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"}},{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9656999707221985,"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/differential-privacy","display_name":"Differential privacy","score":0.8907111883163452},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7979817390441895},{"id":"https://openalex.org/keywords/adversary","display_name":"Adversary","score":0.6724659204483032},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"Crowdsourcing","score":0.5755807757377625},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5461956858634949},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5330482721328735},{"id":"https://openalex.org/keywords/information-privacy","display_name":"Information privacy","score":0.4805084466934204},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46605902910232544},{"id":"https://openalex.org/keywords/information-sensitivity","display_name":"Information sensitivity","score":0.45320749282836914},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4453153908252716},{"id":"https://openalex.org/keywords/optimization-problem","display_name":"Optimization problem","score":0.41266098618507385},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40968361496925354},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4012315571308136},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3247663974761963},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.3089537024497986},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12511807680130005}],"concepts":[{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.8907111883163452},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7979817390441895},{"id":"https://openalex.org/C41065033","wikidata":"https://www.wikidata.org/wiki/Q2825412","display_name":"Adversary","level":2,"score":0.6724659204483032},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.5755807757377625},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5461956858634949},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5330482721328735},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.4805084466934204},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46605902910232544},{"id":"https://openalex.org/C137822555","wikidata":"https://www.wikidata.org/wiki/Q2587068","display_name":"Information sensitivity","level":2,"score":0.45320749282836914},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4453153908252716},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.41266098618507385},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40968361496925354},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4012315571308136},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3247663974761963},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.3089537024497986},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12511807680130005},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/infocom.2019.8737494","is_oa":false,"landing_page_url":"https://doi.org/10.1109/infocom.2019.8737494","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE INFOCOM 2019 - IEEE Conference on Computer Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.46000000834465027,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1524581953","https://openalex.org/W1966072539","https://openalex.org/W1985511977","https://openalex.org/W1992926795","https://openalex.org/W2027595342","https://openalex.org/W2051267297","https://openalex.org/W2053637704","https://openalex.org/W2077217970","https://openalex.org/W2119874464","https://openalex.org/W2248469562","https://openalex.org/W2473418344","https://openalex.org/W2501165858","https://openalex.org/W2532781556","https://openalex.org/W2535690855","https://openalex.org/W2605258322","https://openalex.org/W2763450200","https://openalex.org/W2785361959","https://openalex.org/W2791886312","https://openalex.org/W2793685318","https://openalex.org/W2894150413","https://openalex.org/W2950943617","https://openalex.org/W2963062476","https://openalex.org/W2963541051","https://openalex.org/W2963695762","https://openalex.org/W4205228770","https://openalex.org/W4297799122","https://openalex.org/W6677855611","https://openalex.org/W6728897251","https://openalex.org/W6743732567","https://openalex.org/W6747732332"],"related_works":["https://openalex.org/W4312238270","https://openalex.org/W4309798060","https://openalex.org/W3038085494","https://openalex.org/W2808007232","https://openalex.org/W2964332492","https://openalex.org/W4383469366","https://openalex.org/W4300625486","https://openalex.org/W4213338344","https://openalex.org/W113555067","https://openalex.org/W2989885118"],"abstract_inverted_index":{"With":[0],"the":[1,19,33,52,57,75,83,116,122,136,142,176,189],"amount":[2],"of":[3,21,78,128,138,167],"user":[4,34],"data":[5,8,89],"crowdsourced":[6],"for":[7],"mining":[9],"dramatically":[10],"increasing,":[11],"there":[12],"is":[13,40,63,81,91,172],"an":[14,38,111],"urgent":[15],"need":[16],"to":[17,29,32,43,96,134,141,160],"protect":[18],"privacy":[20,24,90,97,129,162,169,178],"individuals.":[22],"Differential":[23],"mechanisms":[25],"are":[26,100],"conventionally":[27],"adopted":[28],"add":[30],"noise":[31,140,151],"data,":[35],"so":[36],"that":[37,74,82,99,120,153],"adversary":[39],"not":[41,92],"able":[42],"gain":[44],"any":[45,186],"additional":[46],"knowledge":[47],"about":[48],"individuals":[49],"participating":[50],"in":[51,175,188],"crowdsourcing,":[53],"by":[54],"inferring":[55],"from":[56,110],"learned":[58],"model.":[59],"However,":[60],"such":[61],"protection":[62],"usually":[64],"achieved":[65],"with":[66],"significantly":[67],"degraded":[68],"learning":[69,156],"results.":[70],"We":[71,131],"have":[72],"observed":[73],"fundamental":[76],"cause":[77],"this":[79,104,108],"problem":[80,109,117],"relationship":[84],"between":[85],"model":[86,143,190],"utility":[87],"and":[88,114,145,184,192],"accurately":[93],"characterized,":[94],"leading":[95],"constraints":[98],"overly":[101],"strict.":[102],"In":[103],"paper,":[105],"we":[106],"address":[107],"optimization":[112],"perspective,":[113],"formulate":[115],"as":[118],"one":[119],"minimizes":[121],"accuracy":[123,157],"loss":[124],"given":[125],"a":[126,147,165],"set":[127],"constraints.":[130,163],"use":[132],"sensitivity":[133],"describe":[135],"impact":[137],"perturbation":[139],"utility,":[144],"propose":[146],"new":[148],"optimized":[149],"additive":[150],"mechanism":[152],"improves":[154],"overall":[155],"while":[158],"conforming":[159],"individual":[161],"As":[164],"highlight":[166],"our":[168],"mechanism,":[170],"it":[171],"highly":[173],"robust":[174],"high":[177],"regime":[179],"(when":[180],"\u2208":[181],"\u2192":[182],"0),":[183],"against":[185],"changes":[187],"structure":[191],"experimental":[193],"settings.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}