{"id":"https://openalex.org/W4403037846","doi":"https://doi.org/10.1145/3698104","title":"Subsampling Suffices for Adaptive Data Analysis","display_name":"Subsampling Suffices for Adaptive Data Analysis","publication_year":2024,"publication_date":"2024-10-01","ids":{"openalex":"https://openalex.org/W4403037846","doi":"https://doi.org/10.1145/3698104"},"language":"en","primary_location":{"id":"doi:10.1145/3698104","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3698104","pdf_url":null,"source":{"id":"https://openalex.org/S118992489","display_name":"Journal of the ACM","issn_l":"0004-5411","issn":["0004-5411","1557-735X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the ACM","raw_type":"journal-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/A5059516326","display_name":"Guy Blanc","orcid":"https://orcid.org/0000-0003-3185-1097"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Guy Blanc","raw_affiliation_strings":["Computer Science, Stanford University, Stanford, United States"],"affiliations":[{"raw_affiliation_string":"Computer Science, Stanford University, Stanford, United States","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5059516326"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":0.7552,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.75008846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"72","issue":"1","first_page":"1","last_page":"45"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.994700014591217,"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"}},"topics":[{"id":"https://openalex.org/T10136","display_name":"Statistical Methods and Inference","score":0.994700014591217,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9934999942779541,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9926999807357788,"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/computer-science","display_name":"Computer science","score":0.634631335735321}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.634631335735321}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3698104","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3698104","pdf_url":null,"source":{"id":"https://openalex.org/S118992489","display_name":"Journal of the ACM","issn_l":"0004-5411","issn":["0004-5411","1557-735X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the ACM","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1521255013","https://openalex.org/W1531368347","https://openalex.org/W1555759181","https://openalex.org/W1663583528","https://openalex.org/W1963551385","https://openalex.org/W1982723861","https://openalex.org/W1995897489","https://openalex.org/W2033091645","https://openalex.org/W2045086034","https://openalex.org/W2056411324","https://openalex.org/W2063909086","https://openalex.org/W2077641783","https://openalex.org/W2165067615","https://openalex.org/W2167372639","https://openalex.org/W2225981128","https://openalex.org/W2607171573","https://openalex.org/W2622815969","https://openalex.org/W2810715221","https://openalex.org/W2963359984","https://openalex.org/W3157388067","https://openalex.org/W4229035441","https://openalex.org/W4233413206","https://openalex.org/W4234552994","https://openalex.org/W4376639596","https://openalex.org/W6674201379"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"Ensuring":[0],"that":[1,25,100,116,126],"analyses":[2],"performed":[3],"on":[4],"a":[5,42,77,106,140],"dataset":[6,27,43],"are":[7,99],"representative":[8,91],"of":[9,15,30,53,63,81,132,142,159,184,193],"the":[10,16,26,31,38,60,85,96,117,157,180,194],"entire":[11],"population":[12],"is":[13,28,44,122,187],"one":[14],"central":[17],"problems":[18],"in":[19,37,59,120,196],"statistics.":[20],"Most":[21],"classical":[22],"techniques":[23],"assume":[24],"independent":[29],"analyst\u2019s":[32],"query":[33,102,127],"and":[34,69,71,109,171,191],"break":[35],"down":[36],"common":[39],"setting":[40],"where":[41],"reused":[45],"for":[46,165,178],"multiple,":[47],"adaptively":[48],"chosen,":[49],"queries.":[50],"This":[51,113],"problem":[52],"adaptive":[54],"data":[55],"analysis":[56],"was":[57],"formalized":[58],"seminal":[61],"works":[62],"Dwork":[64],"et":[65],"al.":[66],"(STOC":[67],"2015)":[68],"Hardt":[70],"Ullman":[72],"(FOCS":[73],"2014).":[74],"We":[75],"identify":[76],"remarkably":[78],"simple":[79,190],"set":[80],"assumptions":[82],"under":[83],"which":[84],"queries":[86,170,186],"will":[87],"continue":[88],"to":[89,124,138,152],"be":[90],"even":[92],"when":[93],"chosen":[94],"adaptively:":[95],"only":[97],"requirements":[98],"each":[101],"takes":[103],"as":[104],"input":[105],"random":[107],"subsample":[108],"outputs":[110],"few":[111],"bits.":[112],"result":[114],"shows":[115],"noise":[118],"inherent":[119],"subsampling":[121],"sufficient":[123],"guarantee":[125],"responses":[128],"generalize.":[129],"The":[130],"simplicity":[131],"this":[133,160],"subsampling-based":[134],"framework":[135,161],"allows":[136],"it":[137],"model":[139],"variety":[141],"real-world":[143],"scenarios":[144],"not":[145],"covered":[146],"by":[147,162],"prior":[148],"work.":[149],"In":[150,174],"addition":[151],"its":[153],"simplicity,":[154],"we":[155],"demonstrate":[156],"utility":[158],"designing":[163],"mechanisms":[164],"two":[166],"foundational":[167],"tasks:":[168],"statistical":[169,185],"median":[172],"finding.":[173],"particular,":[175],"our":[176],"mechanism":[177],"answering":[179],"broadly":[181],"applicable":[182],"class":[183],"both":[188],"extremely":[189],"state":[192],"art":[195],"many":[197],"parameter":[198],"regimes.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
