{"id":"https://openalex.org/W4229001186","doi":"https://doi.org/10.2478/popets-2022-0041","title":"Differentially Private Simple Linear Regression","display_name":"Differentially Private Simple Linear Regression","publication_year":2022,"publication_date":"2022-03-03","ids":{"openalex":"https://openalex.org/W4229001186","doi":"https://doi.org/10.2478/popets-2022-0041"},"language":"en","primary_location":{"id":"doi:10.2478/popets-2022-0041","is_oa":true,"landing_page_url":"https://doi.org/10.2478/popets-2022-0041","pdf_url":null,"source":{"id":"https://openalex.org/S4210183172","display_name":"Proceedings on Privacy Enhancing Technologies","issn_l":"2299-0984","issn":["2299-0984"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320322","host_organization_name":"De Gruyter Open","host_organization_lineage":["https://openalex.org/P4310320322","https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter Open","De Gruyter"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings on Privacy Enhancing Technologies","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.2478/popets-2022-0041","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043962944","display_name":"Daniel Alabi","orcid":"https://orcid.org/0000-0002-1613-6565"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]},{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Alabi","raw_affiliation_strings":["Harvard John A. Paulson School of Engineering and Applied Sciences","Department of Computer Science, Boston Uni-versity,","College of Computer Sciences, Northeastern University and Department of Computer Science,","School of Engineer-ing and Applied Sciences,","Boston University,","School of Engi-neering and Applied Sciences,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard John A. Paulson School of Engineering and Applied Sciences","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science, Boston Uni-versity,","institution_ids":["https://openalex.org/I111088046"]},{"raw_affiliation_string":"College of Computer Sciences, Northeastern University and Department of Computer Science,","institution_ids":["https://openalex.org/I12912129"]},{"raw_affiliation_string":"School of Engineer-ing and Applied Sciences,","institution_ids":[]},{"raw_affiliation_string":"Boston University,","institution_ids":["https://openalex.org/I111088046"]},{"raw_affiliation_string":"School of Engi-neering and Applied Sciences,","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004893242","display_name":"Audra McMillan","orcid":"https://orcid.org/0000-0003-4231-6110"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Audra McMillan","raw_affiliation_strings":["Khoury College of Computer Sciences , Northeastern University and Department of Computer Science, Boston University","School of Engineering and Applied Sciences,","School of Engi-neering and Applied Sciences,","Boston University,","School of Engineer-ing and Applied Sciences,","Department of Computer Science, Boston Uni-versity,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Khoury College of Computer Sciences , Northeastern University and Department of Computer Science, Boston University","institution_ids":["https://openalex.org/I111088046"]},{"raw_affiliation_string":"School of Engineering and Applied Sciences,","institution_ids":[]},{"raw_affiliation_string":"School of Engi-neering and Applied Sciences,","institution_ids":[]},{"raw_affiliation_string":"Boston University,","institution_ids":["https://openalex.org/I111088046"]},{"raw_affiliation_string":"School of Engineer-ing and Applied Sciences,","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science, Boston Uni-versity,","institution_ids":["https://openalex.org/I111088046"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016878152","display_name":"Jayshree Sarathy","orcid":"https://orcid.org/0000-0001-5852-5182"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]},{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jayshree Sarathy","raw_affiliation_strings":["Harvard John A. Paulson School of Engineering and Applied Sciences","College of Computer Sciences, Northeastern University and Department of Computer Science,","School of Engi-neering and Applied Sciences,","Boston University,","School of Engineer-ing and Applied Sciences,","Department of Computer Science, Boston Uni-versity,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard John A. Paulson School of Engineering and Applied Sciences","institution_ids":[]},{"raw_affiliation_string":"College of Computer Sciences, Northeastern University and Department of Computer Science,","institution_ids":["https://openalex.org/I12912129"]},{"raw_affiliation_string":"School of Engi-neering and Applied Sciences,","institution_ids":[]},{"raw_affiliation_string":"Boston University,","institution_ids":["https://openalex.org/I111088046"]},{"raw_affiliation_string":"School of Engineer-ing and Applied Sciences,","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science, Boston Uni-versity,","institution_ids":["https://openalex.org/I111088046"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079131956","display_name":"Adam Smith","orcid":"https://orcid.org/0000-0002-6744-4592"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]},{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Adam Smith","raw_affiliation_strings":["Department of Computer Science , Boston University","College of Computer Sciences, Northeastern University and Department of Computer Science,","School of Engineer-ing and Applied Sciences,","Department of Computer Science, Boston Uni-versity,","Boston University,","School of Engi-neering and Applied Sciences,","School of Engineering and Applied Sciences,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science , Boston University","institution_ids":["https://openalex.org/I111088046"]},{"raw_affiliation_string":"College of Computer Sciences, Northeastern University and Department of Computer Science,","institution_ids":["https://openalex.org/I12912129"]},{"raw_affiliation_string":"School of Engineer-ing and Applied Sciences,","institution_ids":[]},{"raw_affiliation_string":"Department of Computer Science, Boston Uni-versity,","institution_ids":["https://openalex.org/I111088046"]},{"raw_affiliation_string":"Boston University,","institution_ids":["https://openalex.org/I111088046"]},{"raw_affiliation_string":"School of Engi-neering and Applied Sciences,","institution_ids":[]},{"raw_affiliation_string":"School of Engineering and Applied Sciences,","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016656677","display_name":"Salil Vadhan","orcid":"https://orcid.org/0000-0002-4059-4072"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]},{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Salil Vadhan","raw_affiliation_strings":["Harvard John A. Paulson School of Engineering and Applied Sciences","School of Engineer-ing and Applied Sciences,","College of Computer Sciences, Northeastern University and Department of Computer Science,","Boston University,","Department of Computer Science, Boston Uni-versity,","School of Engi-neering and Applied Sciences,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harvard John A. Paulson School of Engineering and Applied Sciences","institution_ids":[]},{"raw_affiliation_string":"School of Engineer-ing and Applied Sciences,","institution_ids":[]},{"raw_affiliation_string":"College of Computer Sciences, Northeastern University and Department of Computer Science,","institution_ids":["https://openalex.org/I12912129"]},{"raw_affiliation_string":"Boston University,","institution_ids":["https://openalex.org/I111088046"]},{"raw_affiliation_string":"Department of Computer Science, Boston Uni-versity,","institution_ids":["https://openalex.org/I111088046"]},{"raw_affiliation_string":"School of Engi-neering and Applied Sciences,","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2763,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.8207875,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2022","issue":"2","first_page":"184","last_page":"204"},"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/T10845","display_name":"Advanced Causal Inference Techniques","score":0.9531999826431274,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11716","display_name":"Random Matrices and Applications","score":0.9517999887466431,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.7030447721481323},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6237809062004089},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6230378150939941},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.5619438886642456},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.48342716693878174},{"id":"https://openalex.org/keywords/robust-regression","display_name":"Robust regression","score":0.45865556597709656},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.44477224349975586},{"id":"https://openalex.org/keywords/simple-linear-regression","display_name":"Simple linear regression","score":0.44374707341194153},{"id":"https://openalex.org/keywords/ordinary-least-squares","display_name":"Ordinary least squares","score":0.43724334239959717},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42647019028663635},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.41428130865097046},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3382914364337921},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.25353509187698364},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24858638644218445},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2384001910686493}],"concepts":[{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.7030447721481323},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6237809062004089},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6230378150939941},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.5619438886642456},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.48342716693878174},{"id":"https://openalex.org/C70259352","wikidata":"https://www.wikidata.org/wiki/Q1847839","display_name":"Robust regression","level":3,"score":0.45865556597709656},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.44477224349975586},{"id":"https://openalex.org/C149769383","wikidata":"https://www.wikidata.org/wiki/Q7520804","display_name":"Simple linear regression","level":3,"score":0.44374707341194153},{"id":"https://openalex.org/C99656134","wikidata":"https://www.wikidata.org/wiki/Q2912993","display_name":"Ordinary least squares","level":2,"score":0.43724334239959717},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42647019028663635},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.41428130865097046},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3382914364337921},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25353509187698364},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24858638644218445},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2384001910686493},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2478/popets-2022-0041","is_oa":true,"landing_page_url":"https://doi.org/10.2478/popets-2022-0041","pdf_url":null,"source":{"id":"https://openalex.org/S4210183172","display_name":"Proceedings on Privacy Enhancing Technologies","issn_l":"2299-0984","issn":["2299-0984"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320322","host_organization_name":"De Gruyter Open","host_organization_lineage":["https://openalex.org/P4310320322","https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter Open","De Gruyter"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings on Privacy Enhancing Technologies","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.2478/popets-2022-0041","is_oa":true,"landing_page_url":"https://doi.org/10.2478/popets-2022-0041","pdf_url":null,"source":{"id":"https://openalex.org/S4210183172","display_name":"Proceedings on Privacy Enhancing Technologies","issn_l":"2299-0984","issn":["2299-0984"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320322","host_organization_name":"De Gruyter Open","host_organization_lineage":["https://openalex.org/P4310320322","https://openalex.org/P4310313990"],"host_organization_lineage_names":["De Gruyter Open","De Gruyter"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings on Privacy Enhancing Technologies","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G3846745766","display_name":null,"funder_award_id":"CCF-1763786","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3916636108","display_name":"CAREER: A Stable Foundation for Trustworthy Data Analysis","funder_award_id":"1750640","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4320936206","display_name":"AF: Medium: Collaborative Research: Foundations of Adaptive Data Analysis","funder_award_id":"1763786","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4643162613","display_name":"BIGDATA: F: DKA: Scalable, Private Algorithms for Continual Data Analysis","funder_award_id":"1447700","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306151","display_name":"Alfred P. Sloan Foundation","ror":"https://ror.org/052csg198"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1873763122","https://openalex.org/W1980486587","https://openalex.org/W1985511977","https://openalex.org/W1992926795","https://openalex.org/W1997690112","https://openalex.org/W2018764772","https://openalex.org/W2031415694","https://openalex.org/W2096870293","https://openalex.org/W2105584013","https://openalex.org/W2110868467","https://openalex.org/W2123820077","https://openalex.org/W2138865266","https://openalex.org/W2162379889","https://openalex.org/W2896936987","https://openalex.org/W2963699739","https://openalex.org/W2985158452","https://openalex.org/W4239336275"],"related_works":["https://openalex.org/W2127063836","https://openalex.org/W2006385744","https://openalex.org/W3000904183","https://openalex.org/W2001255261","https://openalex.org/W2084530336","https://openalex.org/W4389575561","https://openalex.org/W2274778397","https://openalex.org/W2951481987","https://openalex.org/W1982222006","https://openalex.org/W1501882007"],"abstract_inverted_index":{"Abstract":[0],"Economics":[1],"and":[2,165,221],"social":[3],"science":[4],"research":[5],"often":[6],"require":[7],"analyzing":[8],"datasets":[9,101,130,170],"of":[10,23,91,106,137,148,163,173,208,211,219],"sensitive":[11,33],"personal":[12],"information":[13,67],"at":[14],"fine":[15],"granularity,":[16],"with":[17,65,102],"models":[18],"fit":[19],"to":[20,62,104],"small":[21,100,169],"subsets":[22],"the":[24,69,73,145,149,160,204],"data.":[25],"Unfortunately,":[26],"such":[27],"fine-grained":[28],"analysis":[29,80],"can":[30],"easily":[31],"reveal":[32],"individual":[34,57],"information.":[35],"We":[36,151],"study":[37],"regression":[38,98,122,127],"algorithms":[39,94,154,176],"that":[40,49,143,153],"satisfy":[41],"differential":[42,112],"privacy":[43],",":[44,76],"a":[45,77,87,135,216],"constraint":[46],"which":[47,196,212],"guarantees":[48],"an":[50,63],"algorithm\u2019s":[51],"output":[52],"reveals":[53],"little":[54],"about":[55,68],"any":[56,228],"input":[58],"data":[59],"record,":[60],"even":[61],"attacker":[64],"side":[66],"dataset.":[70],"Motivated":[71],"by":[72],"Opportunity":[74],"Atlas":[75],"high-profile,":[78],"small-area":[79],"tool":[81],"in":[82,195,215,227],"economics":[83],"research,":[84],"we":[85,139,191],"perform":[86,185],"thorough":[88],"experimental":[89,230],"evaluation":[90],"differentially":[92,119,205,233],"private":[93,120,206,234],"for":[95,111,187],"simple":[96],"linear":[97,121,126,235],"on":[99,118,124,128,156,168,178,232],"tens":[103],"hundreds":[105,172],"records\u2014a":[107],"particularly":[108],"challenging":[109],"regime":[110],"privacy.":[113],"In":[114],"contrast,":[115],"prior":[116,229],"work":[117,218,231],"focused":[123],"multivariate":[125],"large":[129,188],"or":[131,182],"asymptotic":[132],"analysis.":[133],"Through":[134],"range":[136],"experiments,":[138],"identify":[140],"key":[141],"factors":[142],"affect":[144],"relative":[146],"performance":[147],"algorithms.":[150],"find":[152],"based":[155,177],"robust":[157],"estimators\u2014in":[158],"particular,":[159],"median-based":[161],"estimator":[162],"Theil":[164],"Sen\u2014perform":[166],"best":[167],"(e.g.,":[171],"datapoints),":[174],"while":[175],"Ordinary":[179],"Least":[180],"Squares":[181],"Gradient":[183],"Descent":[184],"better":[186],"datasets.":[189],"However,":[190],"also":[192],"discuss":[193],"regimes":[194],"this":[197],"general":[198],"finding":[199],"does":[200],"not":[201,224],"hold.":[202],"Notably,":[203],"analogues":[207],"Theil\u2013Sen":[209],"(one":[210],"was":[213],"suggested":[214],"theoretical":[217],"Dwork":[220],"Lei)":[222],"have":[223],"been":[225],"studied":[226],"regression.":[236]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
