{"id":"https://openalex.org/W4380558398","doi":"https://doi.org/10.48550/arxiv.2306.06723","title":"Counting Distinct Elements in the Turnstile Model with Differential Privacy under Continual Observation","display_name":"Counting Distinct Elements in the Turnstile Model with Differential Privacy under Continual Observation","publication_year":2023,"publication_date":"2023-06-11","ids":{"openalex":"https://openalex.org/W4380558398","doi":"https://doi.org/10.48550/arxiv.2306.06723"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2306.06723","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.06723","pdf_url":"https://arxiv.org/pdf/2306.06723","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2306.06723","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101524526","display_name":"Palak Jain","orcid":"https://orcid.org/0009-0005-3806-6974"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jain, Palak","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071129636","display_name":"Iden Kalemaj","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kalemaj, Iden","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080839778","display_name":"Sofya Raskhodnikova","orcid":"https://orcid.org/0000-0002-4902-050X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Raskhodnikova, Sofya","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069926625","display_name":"Satchit Sivakumar","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sivakumar, Satchit","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5079131956","display_name":"Adam Smith","orcid":"https://orcid.org/0000-0002-6744-4592"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Smith, Adam","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101524526"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9994000196456909,"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":0.9994000196456909,"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/T10237","display_name":"Cryptography and Data Security","score":0.9804999828338623,"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/T11719","display_name":"Data Quality and Management","score":0.975600004196167,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/turnstile","display_name":"Turnstile","score":0.9623266458511353},{"id":"https://openalex.org/keywords/differential-privacy","display_name":"Differential privacy","score":0.8595800995826721},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.8258661031723022},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.6596858501434326},{"id":"https://openalex.org/keywords/data-stream","display_name":"Data stream","score":0.5405352115631104},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5341291427612305},{"id":"https://openalex.org/keywords/statistic","display_name":"Statistic","score":0.5322681665420532},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.5235440731048584},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.46913784742355347},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39506080746650696},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36784425377845764},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.27811700105667114},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2307729423046112},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.15814462304115295}],"concepts":[{"id":"https://openalex.org/C31370731","wikidata":"https://www.wikidata.org/wiki/Q7856108","display_name":"Turnstile","level":2,"score":0.9623266458511353},{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.8595800995826721},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.8258661031723022},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.6596858501434326},{"id":"https://openalex.org/C2778484313","wikidata":"https://www.wikidata.org/wiki/Q1172540","display_name":"Data stream","level":2,"score":0.5405352115631104},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5341291427612305},{"id":"https://openalex.org/C89128539","wikidata":"https://www.wikidata.org/wiki/Q1949963","display_name":"Statistic","level":2,"score":0.5322681665420532},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.5235440731048584},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.46913784742355347},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39506080746650696},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36784425377845764},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.27811700105667114},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2307729423046112},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.15814462304115295},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2306.06723","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.06723","pdf_url":"https://arxiv.org/pdf/2306.06723","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2306.06723","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2306.06723","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2306.06723","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.06723","pdf_url":"https://arxiv.org/pdf/2306.06723","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[],"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/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/G6523418542","display_name":"CAREER: Privacy Foundations for Practice and Policy","funder_award_id":"2046425","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6755165505","display_name":null,"funder_award_id":"award","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G794517020","display_name":"Collaborative Research: SaTC: CORE: Small: Foundations for the Next Generation of Private Learning Systems","funder_award_id":"2120667","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","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"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4380558398.pdf"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4389449520","https://openalex.org/W127192698","https://openalex.org/W2570600173","https://openalex.org/W2893008024","https://openalex.org/W2743735673","https://openalex.org/W4361801939","https://openalex.org/W2360131081","https://openalex.org/W2985941356","https://openalex.org/W2802243998","https://openalex.org/W1521014365"],"abstract_inverted_index":{"Privacy":[0],"is":[1,133,152,218,239,246],"a":[2,15,37,48,80,114,123,162,230],"central":[3],"challenge":[4],"for":[5,31,135,140,185,229],"systems":[6],"that":[7,95,100,132,158,216,224],"learn":[8],"from":[9],"sensitive":[10],"data":[11,137],"sets,":[12],"especially":[13],"when":[14],"system's":[16],"outputs":[17,194],"must":[18],"be":[19,53],"continuously":[20],"updated":[21],"to":[22,165,248],"reflect":[23],"changing":[24],"data.":[25],"We":[26,78,93,177,214],"consider":[27],"the":[28,41,72,75,85,126,149,153,159,166,172,175,195,219,241,249,255,259,262],"achievable":[29,221],"error":[30,68,108,146,222,242,253],"differentially":[32,97,181],"private":[33,98,182],"continual":[34],"release":[35],"of":[36,43,74,125,156,161,174,197,212,233,235,243],"basic":[38],"statistic":[39],"-":[40,46],"number":[42,155,196],"distinct":[44,167,198],"items":[45,51],"in":[47,71,84,251,254,261],"stream":[49,76],"where":[50],"may":[52],"both":[54],"inserted":[55],"and":[56,103,139],"deleted":[57],"(the":[58],"turnstile":[59,86,187,263],"model).":[60],"With":[61],"only":[62,226],"insertions,":[63],"existing":[64],"algorithms":[65],"have":[66],"additive":[67,107,206],"just":[69],"polylogarithmic":[70,250],"length":[73],"$T$.":[77],"uncover":[79],"much":[81],"richer":[82],"landscape":[83],"model,":[87],"even":[88,112],"without":[89,208],"considering":[90],"memory":[91],"restrictions.":[92],"show":[94],"every":[96],"mechanism":[99,183,245],"handles":[101],"insertions":[102],"deletions":[104],"has":[105],"worst-case":[106],"at":[109],"least":[110],"$T^{1/4}$":[111],"under":[113],"relatively":[115],"weak,":[116],"event-level":[117],"privacy":[118],"definition.":[119],"Then,":[120],"we":[121,142],"identify":[122],"parameter":[124],"input":[127],"stream,":[128],"its":[129],"maximum":[130,150,190],"flippancy,":[131],"low":[134],"natural":[136],"streams":[138,188],"which":[141],"give":[143],"tight":[144],"parameterized":[145],"guarantees.":[147],"Specifically,":[148],"flippancy":[151,191],"largest":[154],"times":[157],"contribution":[160],"single":[163],"item":[164],"elements":[168,199],"count":[169],"changes":[170],"over":[171],"course":[173],"stream.":[176],"present":[178],"an":[179,201],"item-level":[180],"that,":[184],"all":[186],"with":[189,200],"$w$,":[192,228],"continually":[193],"$O(\\sqrt{w}":[202],"\\cdot":[203],"poly\\log":[204],"T)$":[205],"error,":[207],"requiring":[209],"prior":[210],"knowledge":[211],"$w$.":[213,236],"prove":[215],"this":[217],"best":[220],"bound":[223],"depends":[225],"on":[227],"large":[231],"range":[232],"values":[234],"When":[237],"$w$":[238],"small,":[240],"our":[244],"similar":[247],"$T$":[252],"insertion-only":[256],"setting,":[257],"bypassing":[258],"hardness":[260],"model.":[264]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
