{"id":"https://openalex.org/W4395687285","doi":"https://doi.org/10.48550/arxiv.2404.16706","title":"Efficient and Near-Optimal Noise Generation for Streaming Differential Privacy","display_name":"Efficient and Near-Optimal Noise Generation for Streaming Differential Privacy","publication_year":2024,"publication_date":"2024-04-25","ids":{"openalex":"https://openalex.org/W4395687285","doi":"https://doi.org/10.48550/arxiv.2404.16706"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2404.16706","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.16706","pdf_url":"https://arxiv.org/pdf/2404.16706","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/2404.16706","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109836090","display_name":"Krishnamurthy Krishnamurthy","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Dvijotham, Krishnamurthy","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090074887","display_name":"Dvijotham","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"McMahan, H. Brendan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036870283","display_name":"H. Brendan McMahan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pillutla, Krishna","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016535318","display_name":"Krishna Pillutla","orcid":"https://orcid.org/0000-0002-1262-8466"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Steinke, Thomas","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5090438638","display_name":"Thomas Steinke","orcid":"https://orcid.org/0000-0002-0338-8042"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Thakurta, Abhradeep","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5109836090"],"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/T12146","display_name":"Power Line Communications and Noise","score":0.9840999841690063,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12146","display_name":"Power Line Communications and Noise","score":0.9840999841690063,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9786999821662903,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9733999967575073,"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":0.8831582069396973},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6424692869186401},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5464810132980347},{"id":"https://openalex.org/keywords/differential","display_name":"Differential (mechanical device)","score":0.4629436731338501},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.3985246419906616},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.22502470016479492},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17289575934410095},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09336164593696594},{"id":"https://openalex.org/keywords/aerospace-engineering","display_name":"Aerospace engineering","score":0.0549868643283844}],"concepts":[{"id":"https://openalex.org/C23130292","wikidata":"https://www.wikidata.org/wiki/Q5275358","display_name":"Differential privacy","level":2,"score":0.8831582069396973},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6424692869186401},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5464810132980347},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.4629436731338501},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.3985246419906616},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.22502470016479492},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17289575934410095},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09336164593696594},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0549868643283844},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2404.16706","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.16706","pdf_url":"https://arxiv.org/pdf/2404.16706","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.2404.16706","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2404.16706","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:2404.16706","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2404.16706","pdf_url":"https://arxiv.org/pdf/2404.16706","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":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4395687285.pdf","grobid_xml":"https://content.openalex.org/works/W4395687285.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W3038283795","https://openalex.org/W2604501336","https://openalex.org/W2734500670","https://openalex.org/W2558166297","https://openalex.org/W2315671126","https://openalex.org/W798507144","https://openalex.org/W2964481303","https://openalex.org/W1751413323"],"abstract_inverted_index":{"In":[0],"the":[1,92,98,110,187,194,215,233,248],"task":[2,95],"of":[3,13,25,65,74,96,108,113,162],"differentially":[4,39,56],"private":[5,40,57],"(DP)":[6],"continual":[7,41,58,83,136,174],"counting,":[8,175],"we":[9],"receive":[10],"a":[11,153,160,181,191,228,243],"stream":[12],"increments":[14],"and":[15,50,138,200,222],"our":[16,239],"goal":[17],"is":[18,150,177],"to":[19,91,168,179,206,232,247],"output":[20],"an":[21,71],"approximate":[22],"running":[23],"total":[24],"these":[26],"increments,":[27],"without":[28],"revealing":[29],"too":[30],"much":[31],"about":[32],"any":[33],"specific":[34],"increment.":[35],"Despite":[36],"its":[37],"simplicity,":[38],"counting":[42,59,84,137],"has":[43],"attracted":[44],"significant":[45],"attention":[46],"both":[47],"in":[48,51,63,106,193],"theory":[49,205],"practice.":[52],"Existing":[53],"algorithms":[54,85],"for":[55,100,134,159,172,214,218],"are":[60],"either":[61],"inefficient":[62],"terms":[64,107],"their":[66],"space":[67,144],"usage":[68],"or":[69,142],"add":[70,86],"excessive":[72],"amount":[73],"noise,":[75],"inducing":[76],"suboptimal":[77],"utility.":[78],"The":[79,94],"most":[80],"practical":[81,230],"DP":[82,135,173],"carefully":[87],"correlated":[88],"Gaussian":[89],"noise":[90,102],"values.":[93],"choosing":[97],"covariance":[99],"this":[101,124,170],"can":[103],"be":[104],"expressed":[105],"factoring":[109],"lower-triangular":[111],"matrix":[112,156],"ones":[114],"(which":[115],"computes":[116],"prefix":[117],"sums).":[118],"We":[119,165,197,209],"present":[120],"two":[121],"approaches":[122],"from":[123,203],"class":[125,161],"(for":[126],"different":[127],"parameter":[128],"regimes)":[129],"that":[130,167,185],"achieve":[131,207],"near-optimal":[132],"utility":[133],"only":[139],"require":[140],"logarithmic":[141],"polylogarithmic":[143],"(and":[145],"time).":[146],"Our":[147,235],"first":[148,240],"approach":[149,237,241],"based":[151],"on":[152,190],"space-efficient":[154],"streaming":[155],"multiplication":[157],"algorithm":[158,171],"Toeplitz":[163],"matrices.":[164],"show":[166,223],"instantiate":[169],"it":[176],"sufficient":[178],"find":[180],"low-degree":[182],"rational":[183],"function":[184,217],"approximates":[186],"square":[188],"root":[189],"circle":[192],"complex":[195],"plane.":[196],"then":[198],"apply":[199],"extend":[201],"tools":[202],"approximation":[204],"this.":[208],"also":[210],"derive":[211],"efficient":[212],"closed-forms":[213],"objective":[216],"arbitrarily":[219],"many":[220],"steps,":[221],"direct":[224],"numerical":[225],"optimization":[226],"yields":[227],"highly":[229],"solution":[231],"problem.":[234],"second":[236],"combines":[238],"with":[242],"recursive":[244],"construction":[245],"similar":[246],"binary":[249],"tree":[250],"mechanism.":[251]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2024-04-27T00:00:00"}
